How Early Can We Detect? Detecting Misinformation on Social Media Using User Profiling and Network Characteristics-Reference-Cited by-同舟云学术

How Early Can We Detect? Detecting Misinformation on Social Media Using User Profiling and Network Characteristics

Published:2023 Issue: Volume: Page:174-189
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Ghosh Shreya^ORCID,Mitra Prasenjit

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43427-3_11

Reference26 articles.

1. Allcott, H., Gentzkow, M.: Social media and fake news in the 2016 election. J. Econ. Perspect. 31(2), 211–236 (2017)

2. Asim, Y., Malik, A.K., Raza, B., Shahid, A.R.: A trust model for analysis of trust, influence and their relationship in social network communities. Telematics Inform. 36, 94–116 (2019)

3. Derczynski, L., Bontcheva, K.: Pheme: veracity in digital social networks. In: UMAP Workshops (2014)

4. Ezeakunne, U., Ho, S.M., Liu, X.: Sentiment and retweet analysis of user response for early fake news detection. In: The International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2020), pp. 1–10 (2020)

5. Ghosh, S., Mitra, P., Hausman, B.L.: Evade: exploring vaccine dissenting discourse on twitter. In: epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge discovery at KDD 2022 (2022)

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