Title

Fake news: Fundamental theories, detection strategies and challenges.

Summary

This paper provides a comprehensive overview of fake news research, addressing its challenges and future directions. It discusses the differences between fake news and related concepts like rumors, outlines fundamental theories from various disciplines, and presents a unified framework for detecting fake news. The tutorial also reviews detection strategies, datasets, and models, and highlights challenges for effective fake news detection, particularly in the context of significant events like the 2020 U.S. presidential election.

 

َAuthor

Zhou, X., Zafarani, R., Shu, K., & Liu, H.

Year

2019

َThematic Area

Communication Studies

Topic

Misinformation, disinformation, and malinformation

Country

Global

Region

Global

Misinformation Combatting

Detection of Misinformation

Place Published

Publisher

Journal

DOI

URL

APA 7th End Text Citation

Zhou, X., Zafarani, R., Shu, K., & Liu, H. (2019, January). Fake news: Fundamental theories, detection strategies and challenges. In Proceedings of the twelfth ACM international conference on web search and data mining (pp. 836-837).