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| Misinformation Detection in Social Media |
| Wu Shiyuan1, Dong Qingxing2,3, Song Zhijun1, Zhang Bin4 |
1.School of Information Management, Central China Normal University, Wuhan 430079
2.School of Journalism and Communication, Wuhan University, Wuhan 430072
3.Big Data Institute, Wuhan University, Wuhan 430072
4.School of Information Management, Nanjing University, Nanjing 210023 |
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Abstract Social media has dramatically improved the efficiency of information access, but it has also contributed to the generation and dissemination of misinformation on the Internet. The accurate and quick detection of misinformation to improve the online information environment is an important issue. Inspired by the Information Ecology Theory, this paper expounds on the current problems and relevant detection methods of misinformation from the three perspectives of content, users, and dissemination. Existing detection methods have achieved state-of-the-art results by deep learning methods. However, because of the lack of relevant data in the early stages, studies on the early detection of misinformation are still rare. Additionally, large-scale benchmark datasets for transfer learning and pre-training tasks are yet to be constructed. Moreover, information mining from users needs to be further evaluated.
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Received: 23 August 2021
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