Skip to main content

Colored Petri Net Model for Blocking Misleading Information Propagation in Online Social Networks

  • Conference paper
  • First Online:
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017 (AISI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 639))

Abstract

Rumors and misleading information propagation is one of the open problems in Online Social Networks (OSN) that haven’t mature solutions till now. In this paper, we propose a Colored Petri Net(CPN) model for detecting and blocking misleading information propagation in OSNs. We experimentally simulated and evaluated the effectiveness of our proposed model on dataset of 1003-newsworthy tweets under the trending topic (#ISIS) in Twitter social network. According to Precision, Recall, and Accuracy metrics, our obtained results cleared outperforming in detecting misleading newsworthy tweets compared with other mechanisms in the literature. In addition, verifying the Reachability property of our CPN model proved that detecting and blocking misleading tweets are reachable states according to the firing life-cycle of tokens.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kumar, K.P., Geethakumari, G.: Detecting misinformation in online social networks using cognitive psychology. Hum.-Centric Comput. Inf. Sci. 4(1), 1–22 (2014). Springer

    Article  Google Scholar 

  2. Karlova, N.A., Fisher, K.E.: Plz RT: a social diffusion model of misinformation and disinformation for understanding human information behavior. Inform. Res. 18(1), 1–17 (2013)

    Google Scholar 

  3. Gupta, A., Kumaraguru, P.: Credibility ranking of tweets during high impact events. In: Proceeding of PSOSM 2012 Proceedings of the 1st Workshop on Privacy and Security in Online Social Media (2012)

    Google Scholar 

  4. Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1–167 (2012)

    Article  MathSciNet  Google Scholar 

  5. Torky, M., Babarse, R., Ibrahim, R., Hassanien, A.E., Schaefer, G., Zhu, S.Y.: Credibility investigation of newsworthy tweets using a visualising petri net model. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC), 9–12 October, Budapest, Hungary(2016)

    Google Scholar 

  6. Jensen, K.: Basic Concepts, Analysis Methods and Practical Use, vol. 1. Springer Science & Business Media (2013)

    Google Scholar 

  7. Cstillo, C., Mendoza, M., Poblete, B.: Information credibility on Twitter. In: WWW 2011 International Conference, Information Credibility, 28 March–1 April, Hyderabad, India (2011)

    Google Scholar 

  8. Morris, M.R., Counts, S., Roseway, A., Hoff, A., Schwarz, J.: Tweeting is believing understanding microblog credibility perceptions. In: CSCW 2012 Conference, 11–15 February. ACM, Seattle (2012)

    Google Scholar 

  9. Abbasi, M.A., Liu, H.: Measuring user credibility in social media. In: International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, pp. 441–448. Springer, Heidelberg, April 2013

    Google Scholar 

  10. Nguyen, D.T., Nguyen, N.P., Thai, M.T.: Sources of misinformation in online social networks: who to suspect? Academia (2014)

    Google Scholar 

  11. Qazvinian, V., Rosengren, E., Radev, D.R., Mei, Q.: Rumor has it: identifying misinformation in microblogs. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, pp. 1589–1599. Association for Computational Linguistics, Edinburgh (2011)

    Google Scholar 

  12. Lappas, T., Terzi, E., Gunopulos, D., Mannila, H.: Finding effectors in social networks. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1059–1068, July 2010

    Google Scholar 

  13. Nguyen, N.P., Yan, G., Thai, M.T.: Analysis of misinformation containment in online social networks. Comput. Netw. 57(10), 2133–2146 (2013). Elsevier

    Article  Google Scholar 

  14. Budak, C., Agrawal, D., El Abbadi, A.: Limiting the spread of misinformation in social networks. In: Proceedings of the 20th International Conference on World Wide Web, pp. 665–674. ACM, Hyderabad, March 2011

    Google Scholar 

  15. Simulator functions CPN Tools Homepage, http://cpntools.org/documentation/tasks/simulation/simulator-functions

  16. Gentry, J.: Package Twitter R (2011), http://cran.rproject.org/web/packages/twitterR/twitterR.pdf

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Torky .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Torky, M., Meligy, A., Ibrahim, H., Hassanein, A.E. (2018). Colored Petri Net Model for Blocking Misleading Information Propagation in Online Social Networks. In: Hassanien, A., Shaalan, K., Gaber, T., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017. AISI 2017. Advances in Intelligent Systems and Computing, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-64861-3_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64861-3_56

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64860-6

  • Online ISBN: 978-3-319-64861-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics