Zhang, Danchen and Zadorozhny, Vladimir
(2020)
Fake News Detection Based on Subjective Opinions.
In: 24th European Conference on Advances in Databases and Information Systems, 25-27 August 2020, Lyon, France.
Abstract
Fake news fluctuates social media, leading to harmful consequences. Several types of information could be utilized to detect fake news, such as news content features and news propagation features. In this study, we focus on the user spreading news behaviors on social media platforms and aim to detect fake news more effectively with more accurate data reliability assessment. We introduce Subjective Opinions into reliability evaluation and proposed two new methods. Experiments on two popular real-world datasets, BuzzFeed and PolitiFact, validates that our proposed Subjective Opinions based method can detect fake news more accurately than all existing methods, and another proposed probability based method achieves state-of-art performance.
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| Item Type: |
Conference or Workshop Item
(Paper)
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| Status: |
Published |
| Creators/Authors: |
|
| Date: |
2020 |
| Date Type: |
Publication |
| Journal or Publication Title: |
European Conference on Advances in Databases and Information Systems |
| Event Title: |
24th European Conference on Advances in Databases and Information Systems |
| Event Dates: |
25-27 August 2020 |
| Event Type: |
Conference |
| Schools and Programs: |
School of Computing and Information > Information Science |
| Refereed: |
Yes |
| Date Deposited: |
27 Apr 2021 13:12 |
| Last Modified: |
27 Apr 2021 13:12 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/40801 |
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