Evaluating vulnerability to fake news in social networks: A community health assessment model

Bhavtosh Rath, Wei Gao, Jaideep Srivastava

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

1 Citation (Scopus)

Abstract

Understanding the spread of false information in social networks has gained a lot of recent attention. In this paper, we explore the role community structures play in determining how people get exposed to fake news. Inspired by approaches in epidemiology, we propose a novel Community Health Assessment model, whose goal is to understand the vulnerability of communities to fake news spread. We define the concepts of neighbor, boundary and core nodes of a community and propose appropriate metrics to quantify the vulnerability of nodes (individual-level) and communities (group-level) to spreading fake news. We evaluate our model on communities identified using three popular community detection algorithms for twelve real-world news spreading networks collected from Twitter. Experimental results show that the proposed metrics perform significantly better on the fake news spreading networks than on the true news, indicating that our community health assessment model is effective.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
EditorsFrancesca Spezzano, Wei Chen, Xiaokui Xiao
PublisherAssociation for Computing Machinery, Inc
Pages432-435
Number of pages4
ISBN (Electronic)9781450368681
DOIs
Publication statusPublished - 27 Aug 2019
Event11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 - Vancouver, Canada
Duration: 27 Aug 201930 Aug 2019

Publication series

NameProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019

Conference

Conference11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
CountryCanada
CityVancouver
Period27/8/1930/8/19

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ASJC Scopus subject areas

  • Communication
  • Computer Networks and Communications
  • Information Systems and Management
  • Sociology and Political Science

Cite this

Rath, B., Gao, W., & Srivastava, J. (2019). Evaluating vulnerability to fake news in social networks: A community health assessment model. In F. Spezzano, W. Chen, & X. Xiao (Eds.), Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 (pp. 432-435). (Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3341161.3342920