The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate
Abstract
When a message, such as a piece of news, spreads in social networks, how can we classify it into categories of interests, such as genuine or fake news? Classification of social media content is a fundamental task for social media mining, and most existing methods regard it as a text categorization problem and mainly focus on using content features, such as words and hashtags. However, for many emerging applications like fake news and rumor detection, it is very challenging, if not impossible, to identify useful features from content. For example, intentional spreaders of fake news may manipulate the content to make it look like real news. To address this problem, this paper concentrates on modeling the propagation of messages in a social network. Specifically, we propose a novel approach, TraceMiner, to (1) infer embeddings of social media users with social network structures; and (2) utilize an LSTM-RNN to represent and classify propagation pathways of a message. Since content information is sparse and noisy on social media, adopting TraceMiner allows to provide a high degree of classification accuracy even in the absence of content information. Experimental results on real-world datasets show the superiority over state-of-the-art approaches on the task of fake news detection and news categorization.
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MVAE: Multimodal Variational Autoencoder for Fake News Detection
Khattar, D., Goud, J. S., Gupta, M., & Varma, V. (2019) · The World Wide Web Conference · doi:10.1145/3308558.3313552 · Cited by 799
Fake news, disinformation and misinformation in social media: a review
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Combating Fake News: A Survey on Identification and Mitigation Techniques
Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., & Liu, Y. (2019) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3305260 · Cited by 514
Sahoo, S. R., & Gupta, B. B. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2020.106983 · Cited by 441
Spread of Hate Speech in Online Social Media
Mathew, B., Dutt, R., Goyal, P., & Mukherjee, A. (2019) · Proceedings of the 10th ACM Conference on Web Science · doi:10.1145/3292522.3326034 · Cited by 348
Metadata
- Authors
- Wu, L., & Liu, H.
- Venue
- Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining
- Publisher
- ACM
- Published
- 2018-02-02
- Pages
- 637-645
- OpenAlex
- W2783564496
- Cited by
- 292
- References
- 42
- FWCI
- 130.01
- Type
- conference paper
- Language
- en
- Open access
- closed
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