News Source Credibility Assessment: A Reddit Case Study
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910334664572928 |
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| author | Amini, Arash Bayiz, Yigit Ege Ram, Ashwin Marculescu, Radu Topcu, Ufuk |
| author_facet | Amini, Arash Bayiz, Yigit Ege Ram, Ashwin Marculescu, Radu Topcu, Ufuk |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_10938 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | News Source Credibility Assessment: A Reddit Case Study Amini, Arash Bayiz, Yigit Ege Ram, Ashwin Marculescu, Radu Topcu, Ufuk Computation and Language Social and Information Networks 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. |
| title | News Source Credibility Assessment: A Reddit Case Study |
| topic | Computation and Language Social and Information Networks |
| url | https://arxiv.org/abs/2402.10938 |