Skip to main content

A Survey of Twitter Rumor Spreading Simulations

  • Conference paper
  • First Online:
Computational Collective Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9329))

Abstract

Viral marketing, marketing techniques that use pre-existing social networks, has experienced a significant encouragement in the last years. In this scope, Twitter is the most studied social network in viral marketing and the rumor spread is a widely researched problem. This paper contributes with a survey of research works which study rumor diffusion in Twitter. Moreover, the most useful aspects of these works to build new multi-agent based simulations dealing with this interesting and complex problem are discussed. The main four research lines in rumor dissemination found and discussed in this paper are: exploratory data analysis, rumor detection, epidemiological modeling, and multi-agent based social simulation. The survey shows that the reproducibility in the specialized literature has to be considerably improved. Finally, a free and open-source simulation tool implementing several of the models considered in this survey is presented.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Buchanan, M.: Economics: Meltdown modelling. Nature 460(7256), 680 (2009)

    Article  Google Scholar 

  2. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.: Measuring user influence in twitter: the million follower fallacy. In: 4th International AAAI Conference on Weblogs and Social Media (ICWSM) (2010)

    Google Scholar 

  3. De Domenico, M., Lima, A., Mougel, P., Musolesi, M.: The Anatomy of a Scientific Rumor. Scientific Reports 3, October 2013

    Google Scholar 

  4. Farmer, J.D., Foley, D.: The economy needs agent-based modelling. Nature 460(7256), 685–686 (2009)

    Article  Google Scholar 

  5. Flentge, F., Polani, D., Uthmann, T.: Modelling the emergence of possession norms using memes. J. Artificial Societies and Social Simulation 4

    Google Scholar 

  6. Garcia-Valverde, T., Campuzano, F., Serrano, E., Villa, A., Botia, J.A.: Simulation of human behaviours for the validation of ambient intelligence services: A methodological approach. Journal of Ambient Intelligence and Smart Environments 4(3), 163–181 (2012)

    Google Scholar 

  7. Gatti, M.A.D.C., Appel, A.P., dos Santos, C.N., Pinhanez, C.S., Cavalin, P.R., Neto, S.B.: A simulation-based approach to analyze the information diffusion in microblogging online social network. In: Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World, WSC 2013, pp. 1685–1696. IEEE Press, Piscataway (2013)

    Google Scholar 

  8. Gupta, A., Lamba, H., Kumaraguru, P.: \({\$}\)1.00 per RT #BostonMarathon #PrayForBoston: Analyzing fake content on twitter, San Francisco, CA, September 2013

    Google Scholar 

  9. Gupta, A., Lamba, H., Kumaraguru, P., Joshi, A.: Faking sandy: characterizing and identifying fake images on twitter during hurricane sandy. In: Proceedings of the 22Nd International Conference on World Wide Web Companion, WWW 2013 Companion, pp. 729–736. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva (2013)

    Google Scholar 

  10. Hethcote, H.W.: The mathematics of infectious diseases. SIAM Review 42, 599–653 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  11. Jin, F., Dougherty, E., Saraf, P., Cao, Y., Ramakrishnan, N.: Epidemiological modeling of news and rumors on twitter. In: Proceedings of the 7th Workshop on Social Network Mining and Analysis, SNAKDD 2013, pp. 8:1–8:9. ACM, New York (2013)

    Google Scholar 

  12. Kostka, J., Oswald, Y.A., Wattenhofer, R.: Word of mouth: rumor dissemination in social networks. In: Shvartsman, A.A., Felber, P. (eds.) SIROCCO 2008. LNCS, vol. 5058, pp. 185–196. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  13. Kwon, S., Cha, M., Jung, K., Chen, W., Wang, Y.: Aspects of rumor spreading on a microblog network. In: Jatowt, A., Lim, E.-P., Ding, Y., Miura, A., Tezuka, T., Dias, G., Tanaka, K., Flanagin, A., Dai, B.T. (eds.) SocInfo 2013. LNCS, vol. 8238, pp. 299–308. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  14. Kwon, S., Cha, M., Jung, K., Chen, W., Wang, Y.: Prominent features of rumor propagation in online social media. In: Xiong, H., Karypis, G., Thuraisingham, B.M., Cook, D.J., Wu, X. (eds.) 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7–10, 2013, pp. 1103–1108. IEEE Computer Society (2013)

    Google Scholar 

  15. Li, X., Mao, W., Zeng, D., Wang, F.-Y.: Agent-based social simulation and modeling in social computing. In: Yang, C.C., Chen, H., Chau, M., Chang, K., Lang, S.-D., Chen, P.S., Hsieh, R., Zeng, D., Wang, F.-Y., Carley, K.M., Mao, W., Zhan, J. (eds.) ISI Workshops 2008. LNCS, vol. 5075, pp. 401–412. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  16. Liu, D., Chen, X.: Rumor propagation in online social networks like twitter - a simulation study. In: Proceedings of the 2011 Third International Conference on Multimedia Information Networking and Security, MINES 2011, pp. 278–282. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  17. Mendoza, M., Poblete, B., Castillo, C.: Twitter under crisis: Can we trust what we rt? In: Proceedings of the First Workshop on Social Media Analytics, SOMA 2010, pp. 71–79. ACM, New York (2010)

    Google Scholar 

  18. Nekovee, M., Moreno, Y., Bianconi, G., Marsili, M.: Theory of rumour spreading in complex social networks. Physica A: Statistical Mechanics and its Applications 374(1), 457–470 (2007)

    Article  Google Scholar 

  19. 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, Stroudsburg (2011)

    Google Scholar 

  20. Rand, W., Rust, R.T.: Agent-based modeling in marketing: Guidelines for rigor. International Journal of Research in Marketing 28(3), 181–193 (2011)

    Article  Google Scholar 

  21. Rolla, V.G., Curado, M.: A reinforcement learning-based routing for delay tolerant networks. Engineering Applications of Artificial Intelligence 26(10), 2243–2250 (2013)

    Article  Google Scholar 

  22. Seo, E., Mohapatra, P., Abdelzaher, T.: Identifying rumors and their sources in social networks (2012)

    Google Scholar 

  23. Serrano, E., Moncada, P., Garijo, M., Iglesias, C.A.: Evaluating social choice techniques into intelligent environments by agent based social simulation. Information Sciences 286, 102–124 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  24. Serrano, E., Poveda, G., Garijo, M.: Towards a holistic framework for the evaluation of emergency plans in indoor environments. Sensors 14(3), 4513–4535 (2014)

    Article  Google Scholar 

  25. Serrano, E., Rovatsos, M., Bota, J.A.: Data mining agent conversations: A qualitative approach to multiagent systems analysis. Information Sciences 230, 132–146 (2013)

    Article  MathSciNet  Google Scholar 

  26. Serrano, E., Rovatsos, M., Botia, J.: A qualitative reputation system for multiagent systems with protocol-based communication. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, vol. 1, pp. 307–314. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2012)

    Google Scholar 

  27. Shah, D., Zaman, T.: Rumors in a network: Who’s the culprit? IEEE Transactions on Information Theory 57(8), 5163–5181 (2011)

    Article  MathSciNet  Google Scholar 

  28. Shamshirband, S., Anuar, N.B., Kiah, M.L.M., Patel, A.: An appraisal and design of a multi-agent system based cooperative wireless intrusion detection computational intelligence technique. Engineering Applications of Artificial Intelligence 26(9), 2105–2127 (2013)

    Article  Google Scholar 

  29. Starbird, K., Maddock, J., Orand, M., Achterman, P., Mason, R.M.: Rumors, false flags, and digital vigilantes: Misinformation on twitter after the 2013 boston marathon bombing. In: iConference 2014 Proceedings, pp. 654–662 (2014)

    Google Scholar 

  30. Tisue, S., Wilensky, U.: NetLogo: A Simple Environment for Modeling Complexity (2004)

    Google Scholar 

  31. Tripathy, R.M., Bagchi, A., Mehta, S.: A study of rumor control strategies on social networks. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, CIKM 2010, pp. 1817–1820. ACM, New York (2010)

    Google Scholar 

  32. Valecha, R., Oh, O., Rao, H.R.: An exploration of collaboration over time in collective crisis response during the haiti 2010 earthquake. In: Baskerville, R., Chau, M. (eds.) Proceedings of the International Conference on Information Systems, ICIS 2013, Milano, Italy, December 15–18, 2013. Association for Information Systems (2013)

    Google Scholar 

  33. Weng, L., Menczer, F., Ahn, Y.-Y.: Virality prediction and community structure in social networks. Scientific Reports 3, August 2013

    Google Scholar 

  34. Yang, S.Y., Liu, A., Mo, S.Y.K.: Twitter financial community modeling using agent based simulation. SSRN scholarly paper, Rochester, NY. IEEE Computational Intelligence in Financial Engineering and Economics, London (2013)

    Google Scholar 

  35. Zhao, L., Cui, H., Qiu, X., Wang, X., Wang, J.: \(\{\)SIR\(\}\) rumor spreading model in the new media age. Physica A: Statistical Mechanics and its Applications 392(4), 995–1003 (2013)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Emilio Serrano .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Serrano, E., Iglesias, C.A., Garijo, M. (2015). A Survey of Twitter Rumor Spreading Simulations. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24069-5_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24068-8

  • Online ISBN: 978-3-319-24069-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics