Social network aided plagiarism detection

Aljaž Zrnec,

Aljaž Zrnec

Search for more papers by this author

Dejan Lavbič,

Corresponding Author

Dejan Lavbič

[email protected]

orcid.org/0000-0003-2390-4160

Address for correspondence: Dr Dejan Lavbič, Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, Ljubljana 1000, Slovenia. Email: [email protected]Search for more papers by this author

Aljaž Zrnec,

Aljaž Zrnec

Search for more papers by this author

Dejan Lavbič,

Corresponding Author

Dejan Lavbič

[email protected]

orcid.org/0000-0003-2390-4160

First published: 17 August 2015

https://doi.org/10.1111/bjet.12345

Citations: 3

Share a link

Email
Facebook
Twitter
LinkedIn
Reddit
Wechat

Abstract

The prevalence of different kinds of electronic devices and the volume of content on the Web have increased the amount of plagiarism, which is considered an unethical act. If we want to be efficient in the detection and prevention of these acts, we have to improve today's methods of discovering plagiarism. The paper presents a research study where a framework for the improved detection of plagiarism is proposed. The framework focuses on the integration of social network information, information from the Web, and an advanced semantically enriched visualization of information about authors and documents that enables the exploration of obtained data by seeking of advanced patterns of plagiarism. To support the proposed framework, a special software tool was also developed. The statistical evaluation confirmed that the employment of social network analysis and advanced visualization techniques led to improvements in the confirmation and investigation stages of the plagiarism detection process, thereby enhancing the overall efficiency of the plagiarism detection process.

References

Ðurić, Z. & Gašević, D. (2013). A source code similarity system for plagiarism detection. The Computer Journal, 56, 1, 70–86.
Ali, A. M. E. T., Abdulla, H. M. D. & Snásel, V. (2011). Overview and comparison of plagiarism detection tools. Paper presented at the DATESO 2011: Annual International Workshop on DAtabases, TExts, Specifications and Objects, Pisek, Czech Republic.
Alzahrani, S., Palade, V., Salim, N. & Abraham, A. (2012). Using structural information and citation evidence to detect significant plagiarism cases in scientific publications. Journal of the American Society for Information Science and Technology, 63, 2, 286–312.
Alzahrani, S. M., Salim, N. & Abraham, A. (2012). Understanding plagiarism linguistic patterns, textual features, and detection methods. IEEE Transactions on Systems, Man, and Cybernetics, 42, 2, 133–149.
Balaguer, E. V. (2009). Putting ourselves in SME's shoes: automatic detection of plagiarism by the WCopyFind tool. Paper presented at the SEPLN'09 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse.
Buckley, E. & Cowap, L. (2013). An evaluation of the use of Turnitin for electronic submission and marking and as a formative feedback tool from an educator's perspective. British Journal of Educational Technology, 44, 4, 562–570.
Culwin, F. & Lancaster, T. (2001). Visualising intra-corpal plagiarism. Paper presented at the 5th International Conference on Information Visualisation, London, UK.
Den Ouden, H. & Van Wijk, C. (2011). Plagiarism: punish or prevent? Some experiences with academic copycatting in the Netherlands. Business Communication Quarterly, 74, 2, 196.
Gross, R. & Acquisti, A. (2005). Information revelation and privacy in online social networks. Paper presented at the Proceedings of the 2005 ACM workshop on Privacy in the electronic society, Alexandria, VA, USA.
Hage, J., Rademaker, P. & Vugt, N. (2010). A comparison of plagiarism detection tools: Department of Information and Computing Sciences, Utrecht University.
Hein, J., Zobrist, R., Konrad, C. & Schuepfer, G. (2012). Scientific fraud in 20 falsified anesthesia papers: detection using financial auditing methods. Der Anaesthesist, 61, 6, 543–549.
Hew, K. F. (2011). Students' and teachers' use of Facebook. Computers in Human Behavior, 27, 2, 662–676. doi: 10.1016/j.chb.2010.11.020.
Introna, L. D. & Hayes, N. (2011). On sociomaterial imbrications: what plagiarism detection systems reveal and why it matters. Information and Organization, 21, 2, 107–122.
Joy, M. & Luck, M. (1999). Plagiarism in programming assignments. IEEE Transactions on Education, 42, 2, 129–133.
Junco, R. (2012). Too much face and not enough books: the relationship between multiple indices of Facebook use and academic performance. Computers in Human Behavior, 28, 1, 187–198. doi: 10.1016/j.chb.2011.08.026.
Makuc, Ž. (2013). Methods to assist plagiarism detection (Bachelor of Science, University of Ljubljana, Faculty of Computer and Information Science).
Marsh, B. (2004). Turnitin.com and the scriptural enterprise of plagiarism detection. Computers and Composition, 21, 4, 427–438.
Mazur, E. (2010). Collecting data from social networking Wb sites and blogs. In S. D. Gosling & J. A. Johnson (Eds), Advanced methods for conducting online behavioral research (pp. 77–90). Washington, DC: American Psychological Association.
McKnight, D. H., Lankton, N. & Tripp, J. (2011). Social networking information disclosure and continuance intention: a disconnect. Paper presented at the 44th Hawaii International Conference on System Sciences (HICSS), Kauai, HI.
Mozgovoy, M., Fredriksson, K., White, D., Joy, M. & Sutinen, E. (2005). Fast plagiarism detection system. In M. Consens & G. Navarro (Eds), String processing and information retrieval Vol. 3772 (pp. 267–270). Berlin, Heidelberg: Springer.
Mozgovoy, M., Kakkonen, T. & Cosma, G. (2010). Automatic student plagiarism detection: future perspectives. Journal of Educational Computing Research, 43, 4, 511–531.
Oberreuter, G. & Velásquez, J. D. (2013). Text mining applied to plagiarism detection: the use of words for detecting deviations in the writing style. Expert Systems with Applications, 40, 9, 3756–3763.
Prechelt, L., Malpohl, G. & Philippsen, M. (2002). Finding plagiarisms among a set of programs with JPlag. Journal of Universal Computer Science, 8, 11, 1016–1038.
Rieder, B. (2013). Studying Facebook via data extraction: the Netvizz application. Paper presented at the Proceedings of the 5th Annual ACM Web Science Conference, Paris, France.
Roblyer, M. D., McDaniel, M., Webb, M., Herman, J. & Witty, J. V. (2010). Findings on Facebook in higher education: a comparison of college faculty and student uses and perceptions of social networking sites. Internet and Higher Education, 13, 3, 134–140. doi: 10.1016/j.iheduc.2010.03.002.
Rolfe, V. (2011). Can Turnitin be used to provide instant formative feedback? British Journal of Educational Technology, 42, 4, 701–710.
Schleimer, S., Wilkerson, D. S. & Aiken, A. (2003). Winnowing: local algorithms for document fingerprinting. Paper presented at the ACM SIGMOD International conference on Management of data.
Stein, B., Lipka, N. & Prettenhofer, P. (2011). Intrinsic plagiarism analysis. Language Resources and Evaluation, 45, 1, 63–82.
Šubelj, L., Furlan, Š. & Bajec, M. (2011). An expert system for detecting automobile insurance fraud using social network analysis. Expert Systems with Applications, 38, 1, 1039–1052. doi: 10.1016/j.eswa.2010.07.143.
Underwood, J. & Szabo, A. (2003). Academic offences and e-learning: individual propensities in cheating. British Journal of Educational Technology, 34, 4, 467–477.
Vrhovec, S. L. R., Trkman, M., Kumer, A., Krisper, M. & Vavpotic, D. (2015). Outsourcing as an economic development tool in transition economies: scattered global software development. Information Technology for Development, 21, 3, 445–459. doi: 10.1080/02681102.2013.874316.
Wilson, R. E., Gosling, S. D. & Graham, L. T. (2012). A review of Facebook research in the social sciences. Perspectives on Psychological Science, 7, 3, 203–220. doi: 10.1177/1745691612442904.
Witherspoon, M., Maldonado, N. & Lacey, C. H. (2012). Undergraduates and academic dishonesty. International Journal of Business & Social Science, 3, 1, 76–86.
Youmans, R. J. (2011). Does the adoption of plagiarism-detection software in higher education reduce plagiarism? Studies in Higher Education, 36, 7, 749–761.
Zimmer, M. (2010). “But the data is already public”: on the ethics of research in Facebook. Ethics and Information Technology, 12, 4, 313–325. doi: 10.1007/s10676-010-9227-5.

Citing Literature

Volume48, Issue1

January 2017

Pages 113-128

Social network aided plagiarism detection

Abstract

References

Citing Literature

References

Information

About Wiley Online Library

Help & Support

Opportunities

Connect with Wiley

Social network aided plagiarism detection

Abstract

References

Citing Literature

References

Related

Information