arXiv:2402.10938

News Source Credibility Assessment: A Reddit Case Study

Arash Amini, Yigit Ege Bayiz, Ashwin Ram, Radu Marculescu, Ufuk Topcu

제출 2024-02-07

원문 초록

In the era of social media platforms, identifying the credibility of online content is crucial to combat misinformation. We present the CREDiBERT (CREDibility assessment using Bi-directional Encoder Representations from Transformers), a source credibility assessment model fine-tuned for Reddit submissions focusing on political discourse as the main contribution. We adopt a semi-supervised training approach for CREDiBERT, leveraging Reddit's community-based structure. By encoding submission content using CREDiBERT and integrating it into a Siamese neural network, we significantly improve the binary classification of submission credibility, achieving a 9% increase in F1 score compared to existing methods. Additionally, we introduce a new version of the post-to-post network in Reddit that efficiently encodes user interactions to enhance the binary classification task by nearly 8% in F1 score. Finally, we employ CREDiBERT to evaluate the susceptibility of subreddits with respect to different topics.

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arXiv:2506.21002공통 태그 Binary Classification공식 코드 · Papers with Code

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