Limiting the spread of misinformation in social networks

Ceren Budak, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

336 Citations (Scopus)

Abstract

In this work, we study the notion of competing campaigns in a social network and address the problem of influence limitation where a "bad" campaign starts propagating from a certain node in the network and use the notion of limiting campaigns to counteract the effect of misinformation. The problem can be summarized as identifying a subset of individuals that need to be convinced to adopt the competing (or "good") campaign so as to minimize the number of people that adopt the "bad" campaign at the end of both propagation processes. We show that this optimization problem is NP-hard and provide approximation guarantees for a greedy solution for various definitions of this problem by proving that they are submodular. We experimentally compare the performance of the greedy method to various heuristics. The experiments reveal that in most cases inexpensive heuristics such as degree centrality compare well with the greedy approach. We also study the influence limitation problem in the presence of missing data where the current states of nodes in the network are only known with a certain probability and show that prediction in this setting is a supermodular problem. We propose a prediction algorithm that is based on generating random spanning trees and evaluate the performance of this approach. The experiments reveal that using the prediction algorithm, we are able to tolerate about 90% missing data before the performance of the algorithm starts degrading and even with large amounts of missing data the performance degrades only to 75% of the performance that would be achieved with complete data.

Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on World Wide Web, WWW 2011
Pages665-674
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2011
Externally publishedYes
Event20th International Conference on World Wide Web, WWW 2011 - Hyderabad, India
Duration: 28 Mar 20111 Apr 2011

Other

Other20th International Conference on World Wide Web, WWW 2011
CountryIndia
CityHyderabad
Period28/3/111/4/11

Fingerprint

Computational complexity
Experiments

Keywords

  • Competing campaigns
  • Information cascades
  • Misinformation
  • Social networks
  • Submodular functions
  • Supermodular functions

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Budak, C., Agrawal, D., & Abbadi, A. E. (2011). Limiting the spread of misinformation in social networks. In Proceedings of the 20th International Conference on World Wide Web, WWW 2011 (pp. 665-674) https://doi.org/10.1145/1963405.1963499

Limiting the spread of misinformation in social networks. / Budak, Ceren; Agrawal, Divyakant; Abbadi, Amr El.

Proceedings of the 20th International Conference on World Wide Web, WWW 2011. 2011. p. 665-674.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Budak, C, Agrawal, D & Abbadi, AE 2011, Limiting the spread of misinformation in social networks. in Proceedings of the 20th International Conference on World Wide Web, WWW 2011. pp. 665-674, 20th International Conference on World Wide Web, WWW 2011, Hyderabad, India, 28/3/11. https://doi.org/10.1145/1963405.1963499
Budak C, Agrawal D, Abbadi AE. Limiting the spread of misinformation in social networks. In Proceedings of the 20th International Conference on World Wide Web, WWW 2011. 2011. p. 665-674 https://doi.org/10.1145/1963405.1963499
Budak, Ceren ; Agrawal, Divyakant ; Abbadi, Amr El. / Limiting the spread of misinformation in social networks. Proceedings of the 20th International Conference on World Wide Web, WWW 2011. 2011. pp. 665-674
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