Seminar Users in the Arabic Twitter Sphere
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Abstract (arXiv)
We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity. We develop a framework that can identify such users with 84.4% precision and 76.1% recall. While our dataset is from the Arab region, omitting language-specific features has only a minor impact on classification performance, and thus, our approach could work for detecting seminar users in other parts of the world and in other languages. We further explored a controversial political topic to observe the prevalence and potential potency of such users. In our case study, we found that 25% of the users engaged in the topic are in fact seminar users and their tweets make nearly a third of the on-topic tweets. Moreover, they are often successful in affecting mainstream discourse with coordinated hashtag campaigns.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jul 2017.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1.
5 papers.
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- 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
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- 2022Emojis as Anchors to Detect Arabic Offensive Language and Hate Speechcited by 14
- 2021BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweetscited by 4
- 2023LAraBench: Benchmarking Arabic AI with Large Language Models24 May 2023
- 2022Emojis as Anchors to Detect Arabic Offensive Language and Hate Speech18 Jan 2022
- 2021A Survey on Predicting the Factuality and the Bias of News Media16 Mar 2021
- 2021A Survey on Stance Detection for Mis- and Disinformation Identification27 Feb 2021
- 2021BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets22 Jan 2021