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

Bhavtosh Rath; Wei Gao; Jaideep Srivastava

doi:10.1145/3341161.3342920

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

Bhavtosh Rath, Wei Gao, Jaideep Srivastava

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

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 language	English (US)
Title of host publication	Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
Editors	Francesca Spezzano, Wei Chen, Xiaokui Xiao
Publisher	Association for Computing Machinery, Inc
Pages	432-435
Number of pages	4
ISBN (Electronic)	9781450368681
DOIs	https://doi.org/10.1145/3341161.3342920
State	Published - Aug 27 2019
Event	11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 - Vancouver, Canada Duration: Aug 27 2019 → Aug 30 2019

Publication series

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

Conference

Conference	11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
Country/Territory	Canada
City	Vancouver
Period	8/27/19 → 8/30/19

Bibliographical note

Funding Information:
identify the vulnerable nodes for false news networks with higher precision. Acknowledgement: This work is supported in part by NSF grant III-1422802.

Publisher Copyright:
© 2019 Association for Computing Machinery.

Publisher link

10.1145/3341161.3342920

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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

Evaluating vulnerability to fake news in social networks: A community health assessment model. / Rath, Bhavtosh; Gao, Wei; Srivastava, Jaideep.
Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019. ed. / Francesca Spezzano; Wei Chen; Xiaokui Xiao. Association for Computing Machinery, Inc, 2019. p. 432-435 (Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, Association for Computing Machinery, Inc, pp. 432-435, 11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, Vancouver, Canada, 8/27/19. https://doi.org/10.1145/3341161.3342920

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

Rath, Bhavtosh ; Gao, Wei ; Srivastava, Jaideep. / Evaluating vulnerability to fake news in social networks : A community health assessment model. Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019. editor / Francesca Spezzano ; Wei Chen ; Xiaokui Xiao. Association for Computing Machinery, Inc, 2019. pp. 432-435 (Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019).

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

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