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Writing a Research Paper Conclusion | Step-by-Step Guide

Published on October 30, 2022 by Jack Caulfield . Revised on April 13, 2023.

• Restate the problem statement addressed in the paper
• Summarize your overall arguments or findings
• Suggest the key takeaways from your paper

The content of the conclusion varies depending on whether your paper presents the results of original empirical research or constructs an argument through engagement with sources .

Table of contents

Step 1: restate the problem, step 2: sum up the paper, step 3: discuss the implications, research paper conclusion examples, frequently asked questions about research paper conclusions.

The first task of your conclusion is to remind the reader of your research problem . You will have discussed this problem in depth throughout the body, but now the point is to zoom back out from the details to the bigger picture.

While you are restating a problem you’ve already introduced, you should avoid phrasing it identically to how it appeared in the introduction . Ideally, you’ll find a novel way to circle back to the problem from the more detailed ideas discussed in the body.

For example, an argumentative paper advocating new measures to reduce the environmental impact of agriculture might restate its problem as follows:

Meanwhile, an empirical paper studying the relationship of Instagram use with body image issues might present its problem like this:

“In conclusion …”

Avoid starting your conclusion with phrases like “In conclusion” or “To conclude,” as this can come across as too obvious and make your writing seem unsophisticated. The content and placement of your conclusion should make its function clear without the need for additional signposting.

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Having zoomed back in on the problem, it’s time to summarize how the body of the paper went about addressing it, and what conclusions this approach led to.

Depending on the nature of your research paper, this might mean restating your thesis and arguments, or summarizing your overall findings.

Argumentative paper: Restate your thesis and arguments

In an argumentative paper, you will have presented a thesis statement in your introduction, expressing the overall claim your paper argues for. In the conclusion, you should restate the thesis and show how it has been developed through the body of the paper.

Briefly summarize the key arguments made in the body, showing how each of them contributes to proving your thesis. You may also mention any counterarguments you addressed, emphasizing why your thesis holds up against them, particularly if your argument is a controversial one.

Don’t go into the details of your evidence or present new ideas; focus on outlining in broad strokes the argument you have made.

Empirical paper: Summarize your findings

In an empirical paper, this is the time to summarize your key findings. Don’t go into great detail here (you will have presented your in-depth results and discussion already), but do clearly express the answers to the research questions you investigated.

Describe your main findings, even if they weren’t necessarily the ones you expected or hoped for, and explain the overall conclusion they led you to.

Having summed up your key arguments or findings, the conclusion ends by considering the broader implications of your research. This means expressing the key takeaways, practical or theoretical, from your paper—often in the form of a call for action or suggestions for future research.

Argumentative paper: Strong closing statement

An argumentative paper generally ends with a strong closing statement. In the case of a practical argument, make a call for action: What actions do you think should be taken by the people or organizations concerned in response to your argument?

If your topic is more theoretical and unsuitable for a call for action, your closing statement should express the significance of your argument—for example, in proposing a new understanding of a topic or laying the groundwork for future research.

Empirical paper: Future research directions

In a more empirical paper, you can close by either making recommendations for practice (for example, in clinical or policy papers), or suggesting directions for future research.

Whatever the scope of your own research, there will always be room for further investigation of related topics, and you’ll often discover new questions and problems during the research process .

Finish your paper on a forward-looking note by suggesting how you or other researchers might build on this topic in the future and address any limitations of the current paper.

Full examples of research paper conclusions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

While the role of cattle in climate change is by now common knowledge, countries like the Netherlands continually fail to confront this issue with the urgency it deserves. The evidence is clear: To create a truly futureproof agricultural sector, Dutch farmers must be incentivized to transition from livestock farming to sustainable vegetable farming. As well as dramatically lowering emissions, plant-based agriculture, if approached in the right way, can produce more food with less land, providing opportunities for nature regeneration areas that will themselves contribute to climate targets. Although this approach would have economic ramifications, from a long-term perspective, it would represent a significant step towards a more sustainable and resilient national economy. Transitioning to sustainable vegetable farming will make the Netherlands greener and healthier, setting an example for other European governments. Farmers, policymakers, and consumers must focus on the future, not just on their own short-term interests, and work to implement this transition now.

As social media becomes increasingly central to young people’s everyday lives, it is important to understand how different platforms affect their developing self-conception. By testing the effect of daily Instagram use among teenage girls, this study established that highly visual social media does indeed have a significant effect on body image concerns, with a strong correlation between the amount of time spent on the platform and participants’ self-reported dissatisfaction with their appearance. However, the strength of this effect was moderated by pre-test self-esteem ratings: Participants with higher self-esteem were less likely to experience an increase in body image concerns after using Instagram. This suggests that, while Instagram does impact body image, it is also important to consider the wider social and psychological context in which this usage occurs: Teenagers who are already predisposed to self-esteem issues may be at greater risk of experiencing negative effects. Future research into Instagram and other highly visual social media should focus on establishing a clearer picture of how self-esteem and related constructs influence young people’s experiences of these platforms. Furthermore, while this experiment measured Instagram usage in terms of time spent on the platform, observational studies are required to gain more insight into different patterns of usage—to investigate, for instance, whether active posting is associated with different effects than passive consumption of social media content.

If you’re unsure about the conclusion, it can be helpful to ask a friend or fellow student to read your conclusion and summarize the main takeaways.

• Do they understand from your conclusion what your research was about?
• Are they able to summarize the implications of your findings?
• Can they answer your research question based on your conclusion?

You can also get an expert to proofread and feedback your paper with a paper editing service .

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

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The conclusion of a research paper has several key elements you should make sure to include:

• A restatement of the research problem
• A summary of your key arguments and/or findings
• A short discussion of the implications of your research

No, it’s not appropriate to present new arguments or evidence in the conclusion . While you might be tempted to save a striking argument for last, research papers follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the results and discussion sections if you are following a scientific structure). The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

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A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature

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Paper: Discussion/Conclusion

This article is about the last section that wraps up a paper – it’s often called the “Discussion” in electrical engineering and “Conclusion” in computer science. We will use “Discussion” to refer to both of these, but the article applies to both.

Criteria for Success

A strong Discussion section:

• recaps the main conclusion of the paper in one or two sentences.
• relates the paper’s results to the big questions posed in the Introduction.
• describes how (and why) this work agrees or disagrees with other similar work.
• analyzes how the limitations of this study leave the big questions unanswered.
• puts the work in context – how does it relate to the rest of the literature?
• looks forward at how extensions of this paper’s results will be useful for answering the big questions.

Structure Diagram

Below is one possible structure for a Discussion section.

Identify Your Purpose

The Discussion explains how your work addresses the big questions you posed in your Introduction. The Introduction and Discussion are natural partners. The Introduction tells the reader what question you are working on and your specific approach (e.g. why you did a particular experiment to investigate it, what techniques you used, etc.); the Discussion tells the reader how the results of that approach contribute to answering the bigger question. That is, the Discussion explains how your results address the main questions you set out to answer in the Introduction.

Analyze Your Audience

Different kinds of readers will expect different things from your Discussion. Readers who are not experts in your field might skip your Results and read your Discussion for a high-level description of your results and their importance. They might also be interested to know what you think the future of your field is. Readers who are more familiar with your field will generally understand your results, but they will be curious about how you interpreted confusing, conflicting, or complicated results.

As you write your Discussion, decide who will find each paragraph interesting and what you want them to take away from it. Successful Discussions can simultaneously provide the specific, nuanced information that experts want to read and the broader, more general statements that non-experts can appreciate.

The balance between expert and non-expert readers will depend on the journal or conference you submit to. High-profile, general-readership conferences and journals will have more non-expert readers, while more technical, field-specific conferences and journals can have almost exclusively expert readers.

Recap paper objectives and motivation

In the Introduction, you laid out the objectives of your work and motivated why those objectives solve an important problem. To recap, the Discussion might include a short summary of why the problem this paper addresses is impactful and how solving it with your methodology advances the field.

Set your paper apart from previous work

Weak Discussions begin with a summary of the results or a repetition of the main points of the Introduction. Strong Discussions immediately carve out a place for themselves in the large universe of papers by saying what makes this one interesting or special. For example, the Discussion might describe how the methodology in the paper is unique and useful or how the questions the paper addresses are important and have not yet been directly addressed by other papers. One way to do this is to start the Discussion with one or two sentences that relate the results to the existing literature.

Relate your results to existing results

In the Introduction, you probably helped motivate your study by citing previous results in your field. Now that you’ve laid out your results, you should tell whether your results agree or disagree with prior work and why. You might have extended previous work, showed how apparently conflicting results are actually harmonious, or exposed a contradiction that currently has no explanation. Another strategy is to bring up additional related work in the conclusion and explain how your results might fit into their broader context.

Tell how your study’s limitations leave open the big questions

Every study is finite—you did some things and not others, and you used methods that can explain some phenomena but not others. What bigger questions does your study bring up, and how might those get resolved? Do you just need to do more of the same kind of work? Have you shown that current methods are inadequate to answer the big question, and what more is needed to answer it?

Every paper is a contribution to a larger scientific conversation. To explain this contribution, many Discussions end by placing the paper in an expected future of research in that field. Depending on how much there is to say about future work, this forward-looking description of future work might be a statement or even its own subsection. The discussion of future work might relate the new experiments or techniques in the paper to other problems in the field.

Content adapted by the MIT Electrical Engineering and Computer Science Communication Lab from an article originally created by the MIT Biological Engineering Communication Lab .

Resources and Annotated Examples

Annotated example 1.

Liu et al Nature 2013 760 KB

Annotated Example 2

Schardl et al, ACM SIGPLAN 2017 46 KB

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Top Ten Computer Science Education Research Papers of the Last 50 Years Recognized

At 50th anniversary sigcse symposium, leading computer science education group highlights research that has shaped the field.

New York, NY, March 2, 2019 – As a capstone to its 50th annual SIGCSE Technical Symposium , leaders of the Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE) are celebrating the ideas that have shaped the field by recognizing a select group of publications with a “Top Ten Symposium Papers of All Time Award.” The top ten papers were chosen from among the best papers that were presented at the SIGCSE Technical Symposium over the last 49 years.

As part of the Top Ten announcement today in Minneapolis, the coauthors of each top paper will receive a plaque, free conference registration for one co-author to accept the award and up to a total of $2,000 that can be used toward travel for all authors of the top ranked paper.

“In 1969, the year of our first SIGCSE symposium, computing education was a niche specialty” explains SIGCSE Board Chair Amber Settle of DePaul University, of Chicago, USA. “Today, it is an essential skill students need to prepare for the workforce. Computing has become one of the most popular majors in higher education, and more and more students are being introduced to computing in K-12 settings. The Top Ten Symposium Papers of All Time Award will emphasize the outstanding research that underpins and informs how students of all ages learn computing. We also believe that highlighting excellent research will inspire others to enter the computing education field and make their own contributions.”

The Top Ten Symposium Papers are:

1. “ Identifying student misconceptions of programming ” (2010) Lisa C. Kaczmarczyk, Elizabeth R. Petrick, University of California, San Diego; Philip East, University of Northern Iowa; Geoffrey L. Herman, University of Illinois at Urbana-Champaign Computing educators are often baffled by the misconceptions that their CS1 students hold. We need to understand these misconceptions more clearly in order to help students form correct conceptions. This paper describes one stage in the development of a concept inventory for Computing Fundamentals: investigation of student misconceptions in a series of core CS1 topics previously identified as both important and difficult. Formal interviews with students revealed four distinct themes, each containing many interesting misconceptions.

2. “ Improving the CS1 experience with pair programming ” (2003) Nachiappan Nagappan, Laurie Williams, Miriam Ferzli, Eric Wiebe, Kai Yang, Carol Miller, Suzanne Balik, North Carolina State University Pair programming is a practice in which two programmers work collaboratively at one computer, on the same design, algorithm, or code. Prior research indicates that pair programmers produce higher quality code in essentially half the time taken by solo programmers. The authors organized an experiment to assess the efficacy of pair programming in an introductory Computer Science course. Their results indicate that pair programming creates a laboratory environment conducive to more advanced, active learning than traditional labs; students and lab instructors report labs to be more productive and less frustrating.

3. “ Undergraduate women in computer science: experience, motivation and culture ” (1997) Allan Fisher, Jane Margolis, Faye Miller, Carnegie Mellon University During a year-long study, the authors examined the experiences of undergraduate women studying computer science at Carnegie Mellon University, with a specific eye toward understanding the influences and processes whereby they attach themselves to or detach themselves from the field. This report, midway through the two-year project, recaps the goals and methods of the study, reports on their progress and preliminary conclusions, and sketches their plans for the final year and the future beyond this particular project.

4. “ A Multi-institutional Study of Peer Instruction in Introductory Computing ” (2016) Leo Porter, Beth Simon, University of California, San Diego; Dennis Bouvier, Southern Illinois University; Quintin Cutts, University of Glasgow; Scott Grissom, Grand Valley State University; Cynthia Lee, Stanford University; Robert McCartney, University of Connecticut; Daniel Zingaro, University of Toronto Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants in the classroom. This paper adds to this body of knowledge by examining outcomes from seven introductory programming instructors: three novices to PI and four with a range of PI experience. Through common measurements of student perceptions, the authors provide evidence that introductory computing instructors can successfully implement PI in their classrooms.

5. " The introductory programming course in computer science: ten principles " (1978) G. Michael Schneider, University of Minnesota Schneider describes the crucial goals of any introductory programming course while leaving to the reader the design of a specific course to meet these goals. This paper presents ten essential objectives of an initial programming course in Computer Science, regardless of who is teaching or where it is being taught. Schneider attempts to provide an in-depth, philosophical framework for the course called CS1—Computer Programming 1—as described by the ACM Curriculum Committee on Computer Science.

6. “ Constructivism in computer science education ” (1998) Mordechai Ben-Ari, Weizmann Institute of Science Constructivism is a theory of learning which claims that students construct knowledge rather than merely receive and store knowledge transmitted by the teacher. Constructivism has been extremely influential in science and mathematics education, but not in computer science education (CSE). This paper surveys constructivism in the context of CSE, and shows how the theory can supply a theoretical basis for debating issues and evaluating proposals.

7. “ Using software testing to move students from trial-and-error to reflection-in-action ” (2004) Stephen H. Edwards, Virginia Tech Introductory computer science students have relied on a trial and error approach to fixing errors and debugging for too long. Moving to a reflection in action strategy can help students become more successful. Traditional programming assignments are usually assessed in a way that ignores the skills needed for reflection in action, but software testing promotes the hypothesis-forming and experimental validation that are central to this mode of learning. By changing the way assignments are assessed--where students are responsible for demonstrating correctness through testing, and then assessed on how well they achieve this goal--it is possible to reinforce desired skills. Automated feedback can also play a valuable role in encouraging students while also showing them where they can improve.

8. “ What should we teach in an introductory programming course ” (1974) David Gries, Cornell University Gries argues that an introductory course (and its successor) in programming should be concerned with three aspects of programming: 1. How to solve problems, 2. How to describe an algorithmic solution to a problem, and 3. How to verify that an algorithm is correct. In this paper he discusses mainly the first two aspects. He notes that the third is just as important, but if the first two are carried out in a systematic fashion, the third is much easier than commonly supposed.

9. “ Contributing to success in an introductory computer science course: a study of twelve factors ” (2001) Brenda Cantwell Wilson, Murray State University; Sharon Shrock, Southern Illinois University This study was conducted to determine factors that promote success in an introductory college computer science course. The model included twelve possible predictive factors including math background, attribution for success/failure (luck, effort, difficulty of task, and ability), domain specific self-efficacy, encouragement, comfort level in the course, work style preference, previous programming experience, previous non-programming computer experience, and gender. Subjects included 105 students enrolled in a CS1 introductory computer science course at a midwestern university. The study revealed three predictive factors in the following order of importance: comfort level, math, and attribution to luck for success/failure.

10. “ Teaching objects-first in introductory computer science ” (2003) Stephen Cooper, Saint Joseph's University; Wanda Dann, Ithaca College; Randy Pausch Carnegie Mellon University An objects-first strategy for teaching introductory computer science courses is receiving increased attention from CS educators. In this paper, the authors discuss the challenge of the objects-first strategy and present a new approach that attempts to meet this challenge. The approach is centered on the visualization of objects and their behaviors using a 3D animation environment. Statistical data as well as informal observations are summarized to show evidence of student performance as a result of this approach. A comparison is made of the pedagogical aspects of this new approach with that of other relevant work.

Annual Best Paper Award Announced Today SIGCSE officers also announced the inauguration of an annual SIGCSE Test of Time Award. The first award will be presented at the 2020 SIGCSE Symposium and recognize research publications that have had wide-ranging impact on the field.

About SIGCSE

The Special Interest Group on Computer Science Education of the Association for Computing Machinery (ACM SIGCSE) is a community of approximately 2,600 people who, in addition to their specialization within computing, have a strong interest in the quality of computing education. SIGCSE provides a forum for educators to discuss the problems concerned with the development, implementation, and/or evaluation of computing programs, curricula, and courses, as well as syllabi, laboratories, and other elements of teaching and pedagogy.

ACM, the Association for Computing Machinery , is the world's largest educational and scientific computing society, uniting educators, researchers, and professionals to inspire dialogue, share resources, and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

Contact: Adrienne Decker 585-475-4653 [email protected]

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Computer Science Research Methodologies

This paper discusses the several research methodologies that can be used in Computer Science (CS) and Information Systems (IS). The research methods vary according to the science domain and project field. However a little of research methodologies can be reasonable for Computer Science and Information System.

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It is our immense pleasure to present the April 2018 issue (Volume 16 Number 4) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and digital technologies. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 10569 times and this journal is experiencing steady and healthy growth. Google statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, LinkedIn, Academia.edu and EBSCO among others. A great journal cannot be made great without a dedicated editorial team of editors and reviewers. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to meticulously review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status, making sure we deliver high-quality content to our readers in a timely fashion. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” We would like to thank you, the authors and readers, the content providers and consumers, who have made this journal the best possible. For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 16, No. 4, April 2018 Edition ISSN 1947-5500 © IJCSIS, USA.

It is our great pleasure to present the August 2017 issue (Volume 15 Number 8 Part I & II) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9700 times and the number is quickly increasing. This statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 15, No. 8, August 2017 Edition ISSN 1947-5500 © IJCSIS, USA.

It is our great pleasure to present the December 2017 issue (Volume 15 Number 12) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9800 times and this journal is experiencing steady and healthy growth. Google statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. A great journal cannot be made great without a dedicated editorial team of editors and reviewers. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status, making sure we deliver high-quality content to our readers in a timely fashion. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” We would like to thank you, the authors and readers, the content providers and consumers, who have made this journal the best possible. For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 15, No. 12, December 2017 Edition ISSN 1947-5500 © IJCSIS, USA.

A great journal cannot be made great without a dedicated editorial team of editors and reviewers. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status, making sure we deliver high-quality content to our readers in a timely fashion. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” We would like to thank you, the authors and readers, the content providers and consumers, who have made this journal the best possible. For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 15, No. 12, December 2017 Edition ISSN 1947-5500 © IJCSIS, USA.

It is our great pleasure to present the August 2017 issue (Volume 15 Number 8 Part I & II) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9700 times and the number is quickly increasing. This statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 15, No. 8, August 2017 Edition ISSN 1947-5500 © IJCSIS, USA.

It is our great pleasure to present the December 2017 issue (Volume 15 Number 12) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9800 times and this journal is experiencing steady and healthy growth. Google statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others.

It is our great pleasure to present the October 2017 issue (Volume 15 Number 10 Part I & II) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9750 times and the number is quickly increasing. This statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 15, No. 10, October 2017 Edition ISSN 1947-5500 © IJCSIS, USA.

It is our great pleasure to present the October 2017 issue (Volume 15 Number 10 Part I & II) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 9750 times and the number is quickly increasing. This statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status.

It is our great pleasure to present the May 2016 issue PART 2 (Volume 14 Number 5 Part 2) of the International Journal of Computer Science and Information Security (IJCSIS). High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. According to Google Scholar, up to now papers published in IJCSIS have been cited over 6389 times and the number is quickly increasing. This statistics shows that IJCSIS has established the first step to be an international and prestigious journal in the field of Computer Science and Information Security. There have been many improvements to the processing of papers; we have also witnessed a significant growth in interest through a higher number of submissions as well as through the breadth and quality of those submissions. IJCSIS is indexed in major academic/scientific databases and important repositories, such as: Google Scholar, Thomson Reuters, ArXiv, CiteSeerX, Cornell’s University Library, Ei Compendex, ISI Scopus, DBLP, DOAJ, ProQuest, ResearchGate, Academia.edu and EBSCO among others. On behalf of IJCSIS community and the sponsors, we congratulate the authors and thank the reviewers for their outstanding efforts to review and recommend high quality papers for publication. In particular, we would like to thank the international academia and researchers for continued support by citing papers published in IJCSIS. Without their sustained and unselfish commitments, IJCSIS would not have achieved its current premier status. “We support researchers to succeed by providing high visibility & impact value, prestige and excellence in research publication.” For further questions or other suggestions please do not hesitate to contact us at [email protected]. A complete list of journals can be found at: http://sites.google.com/site/ijcsis/ IJCSIS Vol. 14, No. 5, May 2016 Edition ISSN 1947-5500 © IJCSIS, USA.

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World Conference on Information Systems and Technologies

WorldCIST 2021: Trends and Applications in Information Systems and Technologies pp 13–22 Cite as

Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors

• Phoey Lee Teh   ORCID: orcid.org/0000-0002-7787-1299 19 &
• Peter Heard   ORCID: orcid.org/0000-0002-5135-7822 20  
• Conference paper
• First Online: 29 March 2021

1447 Accesses

1 Citations

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1366)

This study reveals common factors among highly cited papers in the computer sciences. The 500 most cited papers in the computer sciences published between January 2013 and December 2017 were downloaded from the Web of Science (WoS). Data on the number of citations, number of authors, article length and subject sub-discipline were extracted and analyzed in order to identify trends, relationships and common features. Correlations between common factors were analyzed. The 500 papers were cited a total of 10,926 times: the average number of citations per paper was 21.82 citations. A correlation was found between author credibility (defined in terms of the QS University Ranking of the first named author’s affiliation) and the number of citations. Authors from universities ranked 350 or higher were more cited than those from lower ranked universities. Relationships were also found between journal ranking and both the number of authors and the article length. Higher ranked journals tend to have a greater number of authors, but were of shorter length. The article length was also found to be correlated with the number of authors and the QS Subject Ranking of the first author’s affiliation. The proportion of articles in higher ranked journals (journal quartile), the length of articles and the number of citations per page were all found to correlate to the sub-discipline area (Information Systems; Software Engineering; Artificial Intelligence; Interdisciplinary Applications; and Theory and Methods).

• Data search
• Knowledge discovery
• Common factors

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Garfield, E.: Citation analysis as a tool in journal evaluation. Serial Librarian 178 (4060), 471–479 (1972)

Google Scholar  

Hirsch, J.E.: hα: an index to quantify an individual’s scientific leadership. Scientometrics 118 , 673–686 (2019)

CrossRef   Google Scholar  

Cormode, G., Ma, Q., Muthukrishnan, S., Thompson, B.: Socializing the h-index. J. Informetrics 7 (3), 718–721 (2013)

Ayaz, S., Masood, N., Islam, M.A.: Predicting scientific impact based on h-index. Scientometrics 114 (3), 993–1010 (2018)

Noruzi, A.: Impact factor, h-index, i10-index and i20-index of webology. Webology 13 (1), 1–4 (2016)

De Visscher, A.: What does the g-index really measure? J. Am. Soc. Inf. Sci. Technol. 62 (11), 2290–2293 (2011)

QS World University Rankings – Methodology|Top Universities. https://www.topuniversities.com/qs-world-university-rankings/methodology . Accessed 19 June 2019

World University Rankings 2019: methodology | Times Higher Education (THE). https://www.timeshighereducation.com/world-university-rankings/methodology-world-university-rankings-2019 . Accessed 19 June 2019

Thelwall, M.: Dimensions: a competitor to Scopus and the web of science? J. Informetrics 12 (2), 430–435 (2018)

Dorta-González, P., Dorta-González, M.I., Suárez-Vega, R.: An approach to the author citation potential: measures of scientific performance which are invariant across scientific fields. Scientometrics 102 (2), 1467–1496 (2014)

Martin-Martin, A., Orduna-Malea, E., Harzing, A., Lopez-Cozar, E.D.: Can we use Google Scholar to identify highly-cited documents? J. Informetrics 11 (1), 152–163 (2017)

Chang, C.L., McAleer, M., Oxley, L.: Coercive journal self citations, impact factor, journal influence and article influence, mathematics and computers in simulation. Int. Assoc. Math. Comput. Simul. (IMACS) 93 , 190–197 (2013)

Plomp, R.: The highly cited papers of professors as and indicator of a research group’s scientific performance. Scientometrics 29 (3), 377–393 (1994)

Rodríguez-Navarro, A.: A simple index for the high-citation tail of citation distribution to quantify research performance in countries and institutions. PLoS ONE 6 (5), e20510 (2011)

Bitetti, M.S.D., Ferreras, J.A.: Publish (in English) or perish: the effect on citation rate of using languages other than English in scientific publications. Ambio 46 (1), 121–127 (2017)

Akre, O., Barone-Adesi, F., Pattersson, A., Pearce, N., Merletti, F., Richiardi, L.: Differences in citation rates by country of origin for papers published in top-ranked medical journals: do they reflect inequalities in access to publication? J. Epidemiol. Community Health 65 (2), 119–123 (2011)

Hamrick, T.A., Fricker, R.D., Brown, G.G.: Assessing what distinguishes highly cited from less-cited papers published in interfaces. Interfaces 40 (6), 454–464 (2010)

Coupé, T.: Peer review versus citations - an analysis of best paper prizes. Res. Policy 42 (1), 295–301 (2013)

Tahamtan, I., Safipour Afshar, A., Ahamdzadeh, K.: Factors affecting number of citations: a comprehensive review of the literature. Scientometrics 107 (3), 1195–1225 (2016). https://doi.org/10.1007/s11192-016-1889-2

Fox, C.W., Paine, C.E.T., Sauterey, B.: Citations increase with manuscript length, author number, and references cited in ecology journals. Ecol. Evol. 6 (21), 7717–7726 (2016). https://doi.org/10.1002/ece3.2505

Aksnes, D.W., Rip, A.: Researchers’ perceptions of citations’. Res. Policy 38 (6), 895–905 (2009)

Gazni, A., Didegah, F.: Investigating different types of research collaboration and citation impact: a case study of Harvard University’s publications. Scientometrics 87 (2), 251–265 (2011)

Oakleaf, M.: Writing information literacy assessment plans: a guide to best practice. Commun. Inf. Literacy 3 (2), 80–90 (2009)

Petersen, C.G., Aase, G.R., Heiser, D.R.: Journal ranking analyses of operations management research. Int. J. Oper. Prod. Manag. 31 (4), 405–422 (2011)

Baker, S.: Authorship: are the days of the lone research ranger limited? Times Higher Education. https://www.timeshighereducation.com/news/authorship-are-days-lone-research-ranger-numbered . Accessed 03 July 2019

Al-Hidabi, M.D., The, P.L.: Multiple publications: the main reason for the retraction of papers in computer science. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol. 886, pp. 551–526. Springer, Cham (2019)

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Department of Computing and Information Systems, School of Science and Technology, Sunway University, 47500, Sunway City, Malaysia

Phoey Lee Teh

Provost Office, Sunway University, 47500, Sunway City, Malaysia

Peter Heard

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ISEG, University of Lisbon, Lisbon, Portugal

Prof. Álvaro Rocha

College of Engineering, The Ohio State University, Columbus, OH, USA

Dr. Hojjat Adeli

Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

Dr. Gintautas Dzemyda

DCT, Universidade Portucalense, Porto, Portugal

Prof. Fernando Moreira

Department of Information Sciences, University of Sheffield, Lisbon, Portugal

Prof. Ana Maria Ramalho Correia

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Teh, P.L., Heard, P. (2021). Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1366. Springer, Cham. https://doi.org/10.1007/978-3-030-72651-5_2

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How To Write A Computer Science Research Paper: Tips, Topic Ideas, and Advice

Writing a computer science research paper can be a challenging task for college students. But with proper planning and organization, it is a manageable process. Typically, there are a few things that research papers or topics should have. This includes:

• An abstract
• An introduction
• Literature review
• Methodology

If you are tasked with such an assignment, this article is for you. You can use this simple guide. We will cover the key elements of a research paper and go over a few tips. This guide is perfect for students, researchers, and anyone looking to improve their skills in the field of computer science. Let’s find out more.

Tips to Use When Writing A Computer Science Research Paper

Table of Contents

As it has been mentioned before, this is a challenge to most students. However, if you prepare well, it suddenly becomes easy. Without any further ado, here are some tips to help guide you through the process.

Pick a Topic

Choose a topic that interests you. Make sure it is relevant to your field of study. It is crucial whether you say to yourself: I’m writing my paper with Papersowl , or you are doing it on your own. It is important to choose an appealing topic for the work. Write about something with the potential to contribute to the industry.

Do your Research

Before you begin, make sure to conduct extensive research on the topic. This will provide you with the necessary background information you need. It will give you a better understanding of the current trends in the field. ( Klonopin Online )

Thesis Statement

Formulate a clear and concise thesis statement. This should be a brief summary of the main argument or point of your work. It will serve as the foundation for the rest of your assignment. This will guide you when it comes to the organization and paper structure of your work.

Have an Outline

An outline will help you organize your thoughts logically. It will also make it easier for you to identify any gaps in your research. This will ensure that your paper flows smoothly.

It is important to use the proper format. These papers often require the use of specific citation formats. It can be MLA or APA. Make sure to familiarize yourself with the various guidelines and format them correctly.

Data Visualization

Use figures, tables, and diagrams. These elements can help to visualize data and make the paper more engaging. But ensure they are used strategically and are well captioned.

Edit and proofread

Before submitting your paper, make sure to proofread and edit it. This will help you to catch any grammatical or typographical errors. Also, make sure to check for consistency in formatting and citation style.

When you are done, share your research with peers, professors, and experts in the field. They will give you feedback and suggestions that can help improve your work.

Your aim should be to write a well-researched paper that will contribute to the field. This is possible if someone follows these simple tips for computer science students while working on their assignment. It also sets a solid foundation for their future work in computer science.

How to Come Up with Your Computer Science Research Paper Topic Ideas

Coming up with a topic for your paper writing can also be as tough. However, this is an essential step in the process. Coming up with a topic you are comfortable with will make your work easy.  Let’s look at some tips to help you generate suggestions for your computer science research paper.

Staying Updated

Stay current with the latest trends in the field of computer science. Keep up-to-date with recent publications and conference proceedings, among other things. This will give you an idea of what things are currently being researched and can inspire new motives.

Find the Problem

Identify a problem or gap in the current research papers. Look for areas where there is a lack of it or where the groundwork now has not yet provided a solution. This can be an opportunity to contribute to the field. You can feel the gap in doing your work.

Leverage your own experience or expertise in computer science. If you are knowledgeable in a specific computer science area, do a paper on a topic related to that experience. This can be a great way to use your own know-how and skills to make a unique contribution to the field.

Collaboration

Brainstorming with colleagues, peers, and professors can help to generate new inspirations and provide valuable feedback for paper writing.

Look for Interdisciplinary Connections

Consider how your computer science research paper work may be connected to other scientific fields. Examples include subjects like physics, mathematics, biology, and psychology. It can open up new perspectives and bring new insights to your research.

Use Online Tools

There are many online resources available that can help you generate topic suggestions for your research paper. These include databases, journals, and academic websites.

Be Open-minded

Don’t be afraid to explore new suggestions and think outside the box. Sometimes the most unexpected objectives can lead to groundbreaking research.

Advice on Writing a Computer Science Research Paper

It is important to focus on several key elements when doing your research paper. This will make your paper clear, well-written, and it will effectively communicate your findings.

It is important to select a clear and specific research question or hypothesis to guide your study. This makes you focused and on-topic. It is crucial to conduct thorough research to gain a deep understanding of the existing findings on your topic. That way you place your own work in the context of what has already been done. It will also help you to identify gaps in the field that your work can address.

Students should also design a rigorous and appropriate research methodology. Your study will become well-designed. Your data is collected and analyzed in a way that is appropriate for your research question.

Present your findings in a clear and concise manner. That way your readers understand your results and that it makes a meaningful contribution to the field.

Edit and proofread your paper for it to be free of errors and well-written. Your work will be taken seriously and given the attention it deserves.

When working on your computer science research paper, focus on the tips mentioned above. Keep it simple and focused. Avoid using jargon or overly technical language. Stick to one main point or argument throughout your paper. Make sure that your final draft is easy to understand for your target audience. There are a lot of things that can help you make your research paper outstanding. But these are just enough to get you going.

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Categories within Computer Science

• cs.AI - Artificial Intelligence ( new , recent , current month ) Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
• cs.CL - Computation and Language ( new , recent , current month ) Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.
• cs.CC - Computational Complexity ( new , recent , current month ) Covers models of computation, complexity classes, structural complexity, complexity tradeoffs, upper and lower bounds. Roughly includes material in ACM Subject Classes F.1 (computation by abstract devices), F.2.3 (tradeoffs among complexity measures), and F.4.3 (formal languages), although some material in formal languages may be more appropriate for Logic in Computer Science. Some material in F.2.1 and F.2.2, may also be appropriate here, but is more likely to have Data Structures and Algorithms as the primary subject area.
• cs.CE - Computational Engineering, Finance, and Science ( new , recent , current month ) Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
• cs.CG - Computational Geometry ( new , recent , current month ) Roughly includes material in ACM Subject Classes I.3.5 and F.2.2.
• cs.GT - Computer Science and Game Theory ( new , recent , current month ) Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
• cs.CV - Computer Vision and Pattern Recognition ( new , recent , current month ) Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
• cs.CY - Computers and Society ( new , recent , current month ) Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
• cs.CR - Cryptography and Security ( new , recent , current month ) Covers all areas of cryptography and security including authentication, public key cryptosytems, proof-carrying code, etc. Roughly includes material in ACM Subject Classes D.4.6 and E.3.
• cs.DS - Data Structures and Algorithms ( new , recent , current month ) Covers data structures and analysis of algorithms. Roughly includes material in ACM Subject Classes E.1, E.2, F.2.1, and F.2.2.
• cs.DB - Databases ( new , recent , current month ) Covers database management, datamining, and data processing. Roughly includes material in ACM Subject Classes E.2, E.5, H.0, H.2, and J.1.
• cs.DL - Digital Libraries ( new , recent , current month ) Covers all aspects of the digital library design and document and text creation. Note that there will be some overlap with Information Retrieval (which is a separate subject area). Roughly includes material in ACM Subject Classes H.3.5, H.3.6, H.3.7, I.7.
• cs.DM - Discrete Mathematics ( new , recent , current month ) Covers combinatorics, graph theory, applications of probability. Roughly includes material in ACM Subject Classes G.2 and G.3.
• cs.DC - Distributed, Parallel, and Cluster Computing ( new , recent , current month ) Covers fault-tolerance, distributed algorithms, stabilility, parallel computation, and cluster computing. Roughly includes material in ACM Subject Classes C.1.2, C.1.4, C.2.4, D.1.3, D.4.5, D.4.7, E.1.
• cs.ET - Emerging Technologies ( new , recent , current month ) Covers approaches to information processing (computing, communication, sensing) and bio-chemical analysis based on alternatives to silicon CMOS-based technologies, such as nanoscale electronic, photonic, spin-based, superconducting, mechanical, bio-chemical and quantum technologies (this list is not exclusive). Topics of interest include (1) building blocks for emerging technologies, their scalability and adoption in larger systems, including integration with traditional technologies, (2) modeling, design and optimization of novel devices and systems, (3) models of computation, algorithm design and programming for emerging technologies.
• cs.FL - Formal Languages and Automata Theory ( new , recent , current month ) Covers automata theory, formal language theory, grammars, and combinatorics on words. This roughly corresponds to ACM Subject Classes F.1.1, and F.4.3. Papers dealing with computational complexity should go to cs.CC; papers dealing with logic should go to cs.LO.
• cs.GL - General Literature ( new , recent , current month ) Covers introductory material, survey material, predictions of future trends, biographies, and miscellaneous computer-science related material. Roughly includes all of ACM Subject Class A, except it does not include conference proceedings (which will be listed in the appropriate subject area).
• cs.GR - Graphics ( new , recent , current month ) Covers all aspects of computer graphics. Roughly includes material in all of ACM Subject Class I.3, except that I.3.5 is is likely to have Computational Geometry as the primary subject area.
• cs.AR - Hardware Architecture ( new , recent , current month ) Covers systems organization and hardware architecture. Roughly includes material in ACM Subject Classes C.0, C.1, and C.5.
• cs.HC - Human-Computer Interaction ( new , recent , current month ) Covers human factors, user interfaces, and collaborative computing. Roughly includes material in ACM Subject Classes H.1.2 and all of H.5, except for H.5.1, which is more likely to have Multimedia as the primary subject area.
• cs.IR - Information Retrieval ( new , recent , current month ) Covers indexing, dictionaries, retrieval, content and analysis. Roughly includes material in ACM Subject Classes H.3.0, H.3.1, H.3.2, H.3.3, and H.3.4.
• cs.IT - Information Theory ( new , recent , current month ) Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
• cs.LO - Logic in Computer Science ( new , recent , current month ) Covers all aspects of logic in computer science, including finite model theory, logics of programs, modal logic, and program verification. Programming language semantics should have Programming Languages as the primary subject area. Roughly includes material in ACM Subject Classes D.2.4, F.3.1, F.4.0, F.4.1, and F.4.2; some material in F.4.3 (formal languages) may also be appropriate here, although Computational Complexity is typically the more appropriate subject area.
• cs.LG - Machine Learning ( new , recent , current month ) Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
• cs.MS - Mathematical Software ( new , recent , current month ) Roughly includes material in ACM Subject Class G.4.
• cs.MA - Multiagent Systems ( new , recent , current month ) Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
• cs.MM - Multimedia ( new , recent , current month ) Roughly includes material in ACM Subject Class H.5.1.
• cs.NI - Networking and Internet Architecture ( new , recent , current month ) Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
• cs.NE - Neural and Evolutionary Computing ( new , recent , current month ) Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
• cs.NA - Numerical Analysis ( new , recent , current month ) cs.NA is an alias for math.NA. Roughly includes material in ACM Subject Class G.1.
• cs.OS - Operating Systems ( new , recent , current month ) Roughly includes material in ACM Subject Classes D.4.1, D.4.2., D.4.3, D.4.4, D.4.5, D.4.7, and D.4.9.
• cs.OH - Other Computer Science ( new , recent , current month ) This is the classification to use for documents that do not fit anywhere else.
• cs.PF - Performance ( new , recent , current month ) Covers performance measurement and evaluation, queueing, and simulation. Roughly includes material in ACM Subject Classes D.4.8 and K.6.2.
• cs.PL - Programming Languages ( new , recent , current month ) Covers programming language semantics, language features, programming approaches (such as object-oriented programming, functional programming, logic programming). Also includes material on compilers oriented towards programming languages; other material on compilers may be more appropriate in Architecture (AR). Roughly includes material in ACM Subject Classes D.1 and D.3.
• cs.RO - Robotics ( new , recent , current month ) Roughly includes material in ACM Subject Class I.2.9.
• cs.SI - Social and Information Networks ( new , recent , current month ) Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1--J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
• cs.SE - Software Engineering ( new , recent , current month ) Covers design tools, software metrics, testing and debugging, programming environments, etc. Roughly includes material in all of ACM Subject Classes D.2, except that D.2.4 (program verification) should probably have Logics in Computer Science as the primary subject area.
• cs.SD - Sound ( new , recent , current month ) Covers all aspects of computing with sound, and sound as an information channel. Includes models of sound, analysis and synthesis, audio user interfaces, sonification of data, computer music, and sound signal processing. Includes ACM Subject Class H.5.5, and intersects with H.1.2, H.5.1, H.5.2, I.2.7, I.5.4, I.6.3, J.5, K.4.2.
• cs.SC - Symbolic Computation ( new , recent , current month ) Roughly includes material in ACM Subject Class I.1.
• cs.SY - Systems and Control ( new , recent , current month ) cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.

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Computer science articles from across Nature Portfolio

Computer science is the study and development of the protocols required for automated processing and manipulation of data. This includes, for example, creating algorithms for efficiently searching large volumes of information or encrypting data so that it can be stored and transmitted securely.

Large-scale AI language systems display an emergent ability to reason by analogy

Analogical reasoning is a hallmark of human intelligence, as it enables us to flexibly solve new problems without extensive practice. By using a wide range of tests, we demonstrate that GPT-3, a large-scale artificial intelligence language model, is capable of solving difficult analogy problems at a level comparable to human performance.

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101 Best Computer Science Topics for 2023

Any student will know the difficulty that comes with developing and choosing a great topic in computer science. Generally speaking, a good topic should be original, interesting, and challenging. It should push the limits of the field of study while still adequately answering the main questions brought on by the study.

We understand the stress that this may cause students, which is why we’ve dedicated our time to search the web and print resources to find the latest computer science topics that create the biggest waves in the field. Here’s the list of the top computer science research topics for 2023 you can use for an essay or senior thesis :

AP Computer Science Topics for Students Entering College

• How has big data impacted the way small businesses conduct market research?
• Does machine learning negatively impact the way neurons in the brain work?
• Did biotech change how medicine is administered to patients?
• How is human perception affected by virtual reality technologies?
• How can education benefit from using virtual reality in learning?
• Are quantum computers the way of the future or are they just a fad?
• Has the Covid-19 pandemic delayed advancements in computer science?

Computer Science Research Paper Topics for High School

• How successful has distance learning computer tech been in the time of Covid-19?
• Will computer assistance in businesses get rid of customer service needs?
• How has encryption and decryption technology changed in the last 20 years?
• Can AI impact computer management and make it automated?
• Why do programmers avoid making a universal programming language?
• How important are human interactions with computer development?
• How will computers change in the next five to ten years?

Controversial Topics in Computer Science for Grad Students

• What is the difference between math modeling and art?
• How are big-budget Hollywood films being affected by CGI technologies?
• Should students be allowed to use technology in classrooms other than comp science?
• How important is it to limit the amount of time we spend using social media?
• Are quantum computers for personal or home use realistic?
• How are embedded systems changing the business world?
• In what ways can human-computer interactions be improved?

Computer Science Capstone Project Ideas for College Courses

• What are the physical limitations of communication and computation?
• Is SCRUM methodology still viable for software development?
• Are ATMs still secure machines to access money or are they a threat?
• What are the best reasons for using open source software?
• The future of distributed systems and its use in networks?
• Has the increased use of social media positively or negatively affected our relationships?
• How is machine learning impacted by artificial intelligence?

Interesting Computer Science Topics for College Students

• How has Blockchain impacted large businesses?
• Should people utilize internal chips to track their pets?
• How much attention should we pay to the content we read on the web?
• How can computers help with human genes sequencing?
• What can be done to enhance IT security in financial institutions?
• What does the digitization of medical fields mean for patients’ privacy?
• How efficient are data back-up methods in business?

Hot Topics in Computer Science for High School Students

• Is distance learning the new norm for earning postgraduate degrees?
• In reaction to the Covid-19 pandemic should more students take online classes?
• How can game theory aid in the analysis of algorithms?
• How can technology impact future government elections?
• Why are there fewer females in the computer science field?
• Should the world’s biggest operating systems share information?
• Is it safe to make financial transactions online?

Ph.D. Research Topics in Computer Science for Grad Students

• How can computer technology help professional athletes improve performance?
• How have Next Gen Stats changed the way coaches game plan?
• How has computer technology impacted medical technology?
• What impact has MatLab software had in the medical engineering field?
• How does self-adaptable application impact online learning?
• What does the future hold for information technology?
• Should we be worried about addiction to computer technology?

Computer Science Research Topics for Undergraduates

• How has online sports gambling changed IT needs in households?
• In what ways have computers changed learning environments?
• How has learning improved with interactive multimedia and similar technologies?
• What are the psychological perspectives on IT advancements?
• What is the balance between high engagement and addiction to video games?
• How has the video gaming industry changed over the decades?
• Has social media helped or damaged our communication habits?

Research Paper Topics in Computer Science

• What is the most important methodology in project planning?
• How has technology improved people’s chances of winning in sports betting?
• How has artificial technology impacted the U.S. economy?
• What are the most effective project management processes in IT?
• How can IT security systems help the practice of fraud score generation?
• Has technology had an impact on religion?
• How important is it to keep your social networking profiles up to date?

More Computer Science Research Papers Topics

• There is no area of human society that is not impacted by AI?
• How adaptive learning helps today’s professional world?
• Does a computer program code from a decade ago still work?
• How has medical image analysis changed because of IT?
• What are the ethical concerns that come with data mining?
• Should colleges and universities have the right to block certain websites?
• What are the major components of math computing?

Computer Science Thesis Topics for College Students

• How can logic and sets be used in computing?
• How has online gambling impacted in-person gambling?
• How did the 5-G network generation change communication?
• What are the biggest challenges to IT due to Covid-19?
• Do you agree that assembly language is a new way to determine data-mine health?
• How can computer technology help track down criminals?
• Is facial recognition software a violation of privacy rights?

Quick and Easy Computer Science Project Topics

• Why do boys and girls learn the technology so differently?
• How effective are computer training classes that target young girls?
• How does technology affect how medicines are administered?
• Will further advancements in technology put people out of work?
• How has computer science changed the way teachers educate?
• Which are the most effective ways of fighting identify theft?

Excellent Computer Science Thesis Topic Ideas

• What are the foreseeable business needs computers will fix?
• What are the pros and cons of having smart home technology?
• How does computer modernization at the office affect productivity?
• How has computer technology led to more job outsourcing?
• Do self-service customer centers sufficiently provide solutions?
• How can a small business compete without updated computer products?

Computer Science Presentation Topics

• What does the future hold for virtual reality?
• What are the latest innovations in computer science?
• What are the pros and cons of automating everyday life?
• Are hackers a real threat to our privacy or just to businesses?
• What are the five most effective ways of storing personal data?
• What are the most important fundamentals of software engineering?

Even More Topics in Computer Science

• In what ways do computers function differently from human brains?
• Can world problems be solved through advancements in video game technology?
• How has computing helped with the mapping of the human genome?
• What are the pros and cons of developing self-operating vehicles?
• How has computer science helped developed genetically modified foods?
• How are computers used in the field of reproductive technologies?

Our team of academic experts works around the clock to bring you the best project topics for computer science student. We search hundreds of online articles, check discussion boards, and read through a countless number of reports to ensure our computer science topics are up-to-date and represent the latest issues in the field. If you need assistance developing research topics in computer science or need help editing or writing your assignment, we are available to lend a hand all year. Just send us a message “ help me write my thesis ” and we’ll put you in contact with an academic writer in the field.

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Home » Blog » Dissertation » Topics » Computer Science » Computer Science Dissertation Topics (27 Examples) For Research

Computer Science Dissertation Topics (27 Examples) For Research

Mark Jun 12, 2020 Jun 12, 2020 Computer Science No Comments

Computer science is a broad subject, which is creating new research opportunities for students. In this field of study, there are a number of themes and aspects to the study and practically each of them can be used to develop a strong dissertation topic. We have gathered many interesting topics to develop a list of […]

Computer science is a broad subject, which is creating new research opportunities for students. In this field of study, there are a number of themes and aspects to the study and practically each of them can be used to develop a strong dissertation topic.

We have gathered many interesting topics to develop a list of computer science dissertation topics. Choosing the right topic from the list of research topics on computer science can help in carrying out research. The project topics on computer science are presented here.

List of Computer science dissertation topics

Can software programs reduce global energy consumption?

How can modern computer applications be supported by operating?

Exploring the best password management applications.

A literature review of the characteristics of a network.

How can data be transformed into dynamic decision making?

Studying the implementation of dart matches analysis.

Differentiating between different modifications in speech manipulator tool.

Exploring the conflicts in software designing and finding ways to detect and manage them proactively.

How to detect cheating in online games based on the behavioural patterns of users?

To study the importance of privacy of electronic records.

A literature review on software development processes and the elimination of risks.

How to design an information system for a multinational company?

Studying the concept of intelligent marketing.

To explore the GUI Test Suites and its automated repair process.

How can the lens of the camera recognise facial expressions and emotions?

To analyse data mining and gene expression analysis in the context of bioinformatics.

Studying the impact of an integrated robotics STEM course for high school students.

To investigate the concept of fuzzy logic controller design for intelligent robots.

A literature review on the real-time embedded systems: present and future.

Security issues, challenges, and solutions related to cloud computing.

Analysing the educational robotics through a comparative study.

Exploring the impact of bioinformatics on medicine and agriculture.

To study cloud computing: a review of different models and concepts.

Investigating the deep neural networks in the context of computational neuroscience.

What is cryptography? A comparative analysis of modern techniques.

Studying the potential of automatic word comparison for historical linguistics.

A literature review on DNA computing-based authentication techniques and its importance.

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Top 100 Computer Science Research Paper Topics

Feb 17, 2022

Feb 17, 2022 | Topics

Computer science is a popular and rapidly evolving field of study. Almost every month, we receive computer science updates. Every day, programming languages, machines, and systems used in computer science advance. Understanding the changing nature of computer science is critical, particularly if you are taking a computer science course. The only disadvantage of computer science’s ever-changing nature is that things become obsolete faster than we can imagine. Some technologies and programming languages that were developed years ago are now outdated. These progressive changes are critical for computer science scholars, researchers, inventors, and professionals in many ways. For example, students are constantly learning and expanding their knowledge base. However, computer science is a technical subject that necessitates both creativity and intelligence. Many students are having difficulty completing their computer science essays on time, which is one reason why students are being forced to repeat the units they failed. If you are a computer science student and your professor has assigned you a computer science research paper, don’t struggle to develop an exciting topic. We have a comprehensive list of excellent computer science research paper topics for you here at TopicsBase. .Get Writing Help Rated 4.8 out of 5 according to 1. The future of robots and computers 2. Efficient control of data mining using public systems 3. Protect private information with digital network security 4. Common types of computer viruses and how to resolve them 5. A research paper on the upgraded bank and ATM security 6. The usefulness and negatives of wearable technology 7. Practical ways to improve interactions between humans and computers 8. The future of computer software and system architecture 9. The effectiveness and benefits of cloud computing 10. How search engine algorithms work and the benefits 11. Artificial intelligence and its impact on humans 12. Rarely known programming systems and languages 13. Why do we have many computer languages? 14. How businesses benefit from big data analysis? 15. Is time travel real or fiction? 16. The impact of human dependence on technology on the success of traditional business setups 17. The effectiveness and usefulness of open source software 18. The future of implantation chips 19. The relationship between deep learning and neural networks 20. The use of microchips in tracing lost pets. Its side effects 21. The usefulness and benefits of virtual reality 22. Should the actions of ethical hackers being legalized? 23. Is artificial intelligence a threat to the human workforce? 24. Has advanced technology motivated the growth of pornography? 25. How evolving technology may affect the human race a hundred years from now 26. Computer science and time travel. How do they relate? 27. Comparing human perception and virtual reality. The pros and cons 28. Will machine learning go obsolete any time soon? 29. The negative effect of the blockchain technology on traditional currency 30. The advancement of video games. How is the future of video games? 31. Will artificial intelligence affect the quality and smartness of video games? 32. A research paper on computer visualization and graphics 33. Will robots replace the human workforce in the future?

With a passion for education and student empowerment, I create blog content that speaks directly to the needs and interests of students. From study hacks and productivity tips to career exploration and personal development

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