Skip to main content
Log in

A social immunity based approach to suppress rumors in online social networks

  • Original Article
  • Published:
International Journal of Machine Learning and Cybernetics Aims and scope Submit manuscript

Abstract

Online social networks (OSNs) connect people around the globe under one virtual society. It helps people gather, communate and share their common interests. But many times, OSNs are also exploited and eventually become a major platform for rumor or false information propagation. Controlling such rumors in OSNs has been the most challenging research interest in recent days. Since OSNs are a platform of collective behavior, we focus on a collective rumor containment approach to control or eradicate rumors. In this paper, an anti-rumor information spreading approach is proposed to contain rumors collectively by following a bio-inspired immunization method called social immunity. First, A competitive information propagation model called competitive cascade (CC) model that spreads rumor and true information simultaneously is defined. This model continuously updates the trustworthiness of individuals in the network on every communication among the participants of OSNs. Then, the initial spreaders of anti-rumors are identified with the help of the intensity of the rumor in the network as well as the individual’s trustworthiness. Finally, a collective rumor containment approach is applied by considering the cost of rumor containment and a rumor intensity threshold. The proposed approach is compared with recent and well-known rumor control approaches and the results show that the proposed approach is effective in eradicating rumors.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Guille A, Hacid H, Favre C, Zighed DA (2013) Information diffusion in online social networks: a survey. ACM Sigmod Record 42(2):17–28

    Article  Google Scholar 

  2. Muller E, Peres R (2019) The effect of social networks structure on innovation performance: a review and directions for research. Int J Res Mark 36(1):3–19

    Article  Google Scholar 

  3. Bakshy E, Rosenn I, Marlow C, Adamic L (2012) The role of social networks in information diffusion. In: Proceedings of the 21st international conference on World Wide Web, pp 519–528

  4. Wen S, Haghighi MS, Chen C, Xiang Y, Zhou W, Jia W (2015) A sword with two edges: propagation studies on both positive and negative information in online social networks. IEEE Trans Comput 64(3):640–653

    Article  MathSciNet  Google Scholar 

  5. Doerr B, Fouz M, Friedrich T (2011) Social networks spread rumors in sublogarithmic time. In: Proceedings of the forty-third annual ACM symposium on Theory of computing, pp 21–30

  6. Friggeri A, Adamic L, Eckles D, Cheng J (2014) Rumor cascades. In: Eighth International AAAI Conference on Weblogs and Social Media

  7. Allport GW, Postman L (1947 The psychology of rumor. Henry Holt

  8. Chen W, Zhang Y, Yeo CK, Lau CT, Lee BS (2018) Unsupervised rumor detection based on users’ behaviors using neural networks. Pattern Recogn Lett 105:226–233

    Article  Google Scholar 

  9. Luo W, Tay WP, Leng M (2013) Identifying infection sources and regions in large networks. IEEE Trans Signal Process 61(11):2850–2865

    Article  MathSciNet  Google Scholar 

  10. Thakur HK, Gupta A, Bhardwaj A, Verma D (2018) Rumor detection on twitter using a supervised machine learning framework. Int J Inf Retrieval Res (IJIRR) 8(3):1–13

    Google Scholar 

  11. Wu K, Yang S, Zhu KQ (2015) False rumors detection on sina weibo by propagation structures. In: 2015 IEEE 31st international conference on data engineering, pp 651–662

  12. Kostka J, Oswald YA, Wattenhofer R (2008) Word of mouth: rumor dissemination in social networks. In: International colloquium on structural information and communication complexity, pp 185–196

  13. Fan L, Lu Z, Wu W, Thuraisingham B, Ma H, Bi Y (2013) Least cost rumor blocking in social networks. In: Distributed Computing Systems (ICDCS), 2013 IEEE 33rd International Conference on, pp 540–549

  14. Hu Y, Pan Q, Hou W, He M (2018) Rumor spreading model considering the proportion of wisemen in the crowd. Phys A 505:1084–1094

    Article  Google Scholar 

  15. Kotnis BA (2014) Cost effective rumor containment in social networks. arXiv preprint 1403.6315.

  16. Li L, Scaglione A, Swami A, Zhao Q (2013) Consensus, polarization and clustering of opinions in social networks. IEEE J Sel Areas Commun 31(6):1072–1083

    Article  Google Scholar 

  17. Wang J, Zhao L, Huang R (2014) SIRaRu rumor spreading model in complex networks. Phys A 398:43–55

    Article  MathSciNet  Google Scholar 

  18. Zhao L, Cui H, Qiu X, Wang X, Wang J (2013) SIR rumor spreading model in the new media age. Phys A Stat Mech Appl 392(4):995–1003

    Article  MathSciNet  Google Scholar 

  19. Starks PT, Blackie CA, Seeley TD (2000) Fever in honeybee colonies. Naturwissenschaften 87(5):229–231

    Article  Google Scholar 

  20. Morente-Molinera JA, Kou G, Peng Y, Torres-Albero C, Herrera-Viedma E (2018) Analysing discussions in social networks using group decision making methods and sentiment analysis. Inf Sci 447:157–168

    Article  Google Scholar 

  21. Morente-Molinera JA, Kou G, Samuylov K, Ureña R, Herrera-Viedma E (2019) Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions. Knowl Based Syst 165:335–345

    Article  Google Scholar 

  22. Li L, Scaglione A, Swami A, Zhao Q (2012) Phase transition in opinion diffusion in social networks. In: Acoustics, speech and signal processing (ICASSP), 2012 IEEE international conference on, pp 3073–3076

  23. Oh O, Agrawal M, Rao HR (2013) Community intelligence and social media services: a rumor theoretic analysis of tweets during social crises. MIS Q 37(2):407–426

    Article  Google Scholar 

  24. Nekovee M, Moreno Y, Bianconi G, Marsili M (2007) Theory of rumour spreading in complex social networks. Phys A 374(1):457–470

    Article  Google Scholar 

  25. Li S, Zhu Y, Li D, Kim D, Huang H (2013) Rumor restriction in online social networks. In: 2013 IEEE 32nd International Performance Computing and Communications Conference (IPCCC), pp 1–10

  26. Fan L, Wu W, Zhai X, Xing K, Lee W, Du D-Z (2014) Maximizing rumor containment in social networks with constrained time. Social Netw Anal Mining 4(1):214

    Article  Google Scholar 

  27. Tong GA, Wu W, Guo L, Li D, Liu C, Liu B, Du DZ (2017) An efficient randomized algorithm for rumor blocking in online social networks. In: IEEE INFOCOM 2017-IEEE conference on computer communications. IEEE, pp 1–9

  28. Tripathy RM, Bagchi A, Mehta S (2010) A study of rumor control strategies on social networks. In: Proceedings of the 19th ACM international conference on Information and knowledge management, pp 1817–1820

  29. Huo L, Song N (2016) Dynamical interplay between the dissemination of scientific knowledge and rumor spreading in emergency. Phys A 461:73–84

    Article  MathSciNet  Google Scholar 

  30. Liu W, Yue K, Wu H, Li J, Liu D, Tang D (2016) Containment of competitive influence spread in social networks. Knowl-Based Syst 109:266–275

    Article  Google Scholar 

  31. He X, Song G, Chen W, Jiang Q (2012) Influence blocking maximization in social networks under the competitive linear threshold model. In: Proceedings of the 2012 SIAM International Conference on Data Mining, pp 463–474

  32. Li K, Zhang L, Huang H (2018) Social influence analysis: models, methods, and evaluation. Engineering 4(1):40–46

    Article  Google Scholar 

  33. Kimura M, Saito K, Motoda H (2009) Blocking links to minimize contamination spread in a social network. ACM Trans Knowl Discov Data (TKDD) 3(2):9

    Google Scholar 

  34. Afassinou K (2014) Analysis of the impact of education rate on the rumor spreading mechanism. Phys A 414:43–52

    Article  MathSciNet  Google Scholar 

  35. Daley DJ, Kendall DG (1964) Epidemics and rumours. Nature 204(4963):1118

    Article  Google Scholar 

  36. Zhao L, Wang Q, Cheng J, Chen Y, Wang J, Huang W (2011) Rumor spreading model with consideration of forgetting mechanism: a case of online blogging LiveJournal. Phys A Stat Mech Appl 390(13):2619–2625

    Article  Google Scholar 

  37. Zhao L, Wang J, Chen Y, Wang Q, Cheng J, Cui H (2012) SIHR rumor spreading model in social networks. Phys A Stat Mech Appl 391(7):2444–2453

    Article  Google Scholar 

  38. Chen G (2019) ILSCR rumor spreading model to discuss the control of rumor spreading in emergency. Phys A 522:88–97

    Article  MathSciNet  Google Scholar 

  39. Pan C, Yang L-X, Yang X, Wu Y, Tang YY (2018) An effective rumor-containing strategy. Phys A 500:80–91

    Article  MathSciNet  Google Scholar 

  40. Weisbuch G, Deffuant G, Amblard F, Nadal JP (2003) Interacting agents and continuous opinions dynamics. In: Heterogenous agents, interactions and economic performance. Springer, Berlin, Heidelberg, pp 225–242

  41. Xia W, Cao M, Johansson KH (2015) Structural balance and opinion separation in trust–mistrust social networks. IEEE Trans Control Netw Syst 3(1):46–56

    Article  MathSciNet  Google Scholar 

  42. Cremer S, Armitage SA, Schmid-Hempel P (2007) Social immunity. Curr Biol 17(16):R693–R702

    Article  Google Scholar 

  43. Bailey L (1968) Honey bee pathology. Annu Rev Entomol 13(1):191–212

    Article  Google Scholar 

  44. Traniello JF, Rosengaus RB, Savoie K (2002) The development of immunity in a social insect: evidence for the group facilitation of disease resistance. Proc Natl Acad Sci 99(10):6838–6842

    Article  Google Scholar 

  45. SNAP (2019) Standford datasets. http://snap.stanford.edu/

  46. Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33:452–473

    Article  Google Scholar 

  47. Hagberg AA, Schult DA, Swart PJ (2008) Exploring network structure, dynamics, and function using networkx. In: Proceedings of the 7th Python in science conference. Varoquaux and Travis Vaught and Jarrod Millman, pp 11–15

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dhinesh Babu L D.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srinivasan, S., L D, D. A social immunity based approach to suppress rumors in online social networks. Int. J. Mach. Learn. & Cyber. 12, 1281–1296 (2021). https://doi.org/10.1007/s13042-020-01233-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-020-01233-0

Keywords

Navigation