Tahaqqaq: A Real-Time System for Assisting Twitter Users in Arabic Claim Verification
Author | Ali, Zien Sheikh |
Author | Mansour, Watheq |
Author | Haouari, Fatima |
Author | Hasanain, Maram |
Author | Elsayed, Tamer |
Author | Al-Ali, Abdulaziz |
Available date | 2023-11-23T07:18:15Z |
Publication Date | 2023-07-19 |
Publication Name | SIGIR 2023 - Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval |
Identifier | http://dx.doi.org/10.1145/3539618.3591815 |
Citation | Sheikh Ali, Z., Mansour, W., Haouari, F., Hasanain, M., Elsayed, T., & Al-Ali, A. (2023, July). Tahaqqaq: a real-time system for assisting twitter users in Arabic claim verification. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 3170-3174). |
ISBN | 9781450394086 |
Abstract | Over the past years, notable progress has been made towards fighting misinformation spread over social media, encouraging the development of many fact-checking systems. However, systems that operate over Arabic content are scarce. In this work, we bridge this gap by proposing Tahaqqaq (Verify), an Arabic real-time system that helps users verify claims over Twitter with several functionalities, such as identifying check-worthy claims, estimating credibility of users in terms of spreading fake news, and finding authoritative accounts. Tahaqqaq has a friendly online Web interface that supports various real-time user scenarios. In the same breath, we enable public access to Tahaqqaq services through a handy RESTful API. Finally, in terms of performance, multiple components of Tahaqqaq outperform the state-of-the-art models on Arabic datasets. |
Sponsor | This work was supported by NPRP grant# NPRP11S-1204-170060 from the Qatar National Research Fund (a member of Qatar Foundation). The work of Fatima Haouari was supported by GSRA grant# GSRA6-1-0611-19074 from the Qatar National Research Fund. The statements made herein are solely the responsibility of the authors. |
Language | en |
Publisher | Association for Computing Machinery, Inc |
Subject | Fact-checking Fake news detection Misinformation Rumors Social media User interface |
Type | Conference Paper |
Pagination | 3170-3174 |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
-
Computer Science & Engineering [2402 items ]