ExFake: Towards an Explainable Fake News Detection Based on Content and Social Context Information

• URL: http://arxiv.org/abs/2311.10784v1
• Date: Thu, 16 Nov 2023 15:57:58 GMT
• Title: ExFake: Towards an Explainable Fake News Detection Based on Content and Social Context Information
• Authors: Sabrine Amri, Henri-Cedric Mputu Boleilanga, Esma A\"imeur
• Abstract summary: ExFake is an explainable fake news detection system based on content and context-level information. An Explainable AI (XAI) assistant is also adopted to help online social networks (OSN) users develop good reflexes when faced with doubted information.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: ExFake is an explainable fake news detection system based on content and context-level information. It is concerned with the veracity analysis of online posts based on their content, social context (i.e., online users' credibility and historical behaviour), and data coming from trusted entities such as fact-checking websites and named entities. Unlike state-of-the-art systems, an Explainable AI (XAI) assistant is also adopted to help online social networks (OSN) users develop good reflexes when faced with any doubted information that spreads on social networks. The trustworthiness of OSN users is also addressed by assigning a credibility score to OSN users, as OSN users are one of the main culprits for spreading fake news. Experimental analysis on a real-world dataset demonstrates that ExFake significantly outperforms other baseline methods for fake news detection.

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