News Source Credibility Assessment: A Reddit Case Study
February 07, 2024 ยท Declared Dead ยท ๐ International Conference on Web and Social Media
"No code URL or promise found in abstract"
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Authors
Arash Amini, Yigit Ege Bayiz, Ashwin Ram, Radu Marculescu, Ufuk Topcu
arXiv ID
2402.10938
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
4
Venue
International Conference on Web and Social Media
Last Checked
5 months ago
Abstract
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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