• Narrative Style and the Spread of Health Misinformation on Twitter
    Achyutarama Ganti, Eslam Hussein, Steven Wilson, Zexin Ma, Xinyan Zhao. In In Findings of the Association for Computational Linguistics: EMNLP 2023. . October 2023. Paper
    • Description: Using a narrative style is an effective way to communicate health information both on and off social media. Given the amount of misinformation being spread online and its potential negative effects, it is crucial to investigate the interplay between narrative communication style and misinformative health content on user engagement on social media platforms. To explore this in the context of Twitter, we start with previously annotated health misinformation tweets (n ≈15,000) and annotate a subset of the data (n=3,000) for the presence of narrative style. We then use these manually assigned labels to train text classifiers, experimenting with supervised fine-tuning and in-context learning for automatic narrative detection. We use our best model to label remaining portion of the dataset, then statistically analyze the relationship between narrative style, misinformation, and user-level features on engagement, finding that narrative use is connected to increased tweet engagement and can, in some cases, lead to increased engagement with misinformation. Finally, we analyze the general categories of language used in narratives and health misinformation in our dataset.

  • Investigating Misinformation in Online Marketplaces: An Audit Study on Amazon
    Eslam Hussein, Hoda Eldardiry. At arXiv . September 2020. Paper
    • Description: We audit Amazon to investigate whether personalization based on user history with the platform contributes to amplifying misinformation present in search results and recommendations. While user activities (searching, browsing, adding items to wishlist or shopping cart) do not have a significant effect, once a user interacts with items that have a misinformation stance toward vaccines (promoting, neutral, or opposing vaccines' misinformation), a filter bubble of misinformative recommendations is built in the user's homepage.

  • Measuring Misinformation in Video Search Platforms: An Audit Study on YouTube
    Eslam Hussein, Prerna Juneja, Tanushree Mitra. In Proceedings of ACM Human Computer Interaction (CSCW'20). Vol. 4 (38) . 2020. Paper
    • Description: We audit YouTube to investigate whether personalization (based on age, gender, geolocation, or watch history) contributes to amplifying misinformation. While demographics do not have a significant effect, once a user develops a watch history, it affects the extent of misinformation recommended to them.

  • Auditing YouTube for Misinformation
    Eslam Hussein, Viral Pasad, Tanushree Mitra. Poster accepted at the Fourth Annual Virginia Tech Workshop on the Future of Human-Computer Interaction: Algorithms that make you think. April 2019. Poster
    • Description: In this work, we audit the YouTube recommendation system for recommending and spreading misinformation such as conspiracy theories, fake news, rumors, and falsified information. In our work, we experiment with YouTube from different angles and study its recommendation of misinformation from different perspectives (demographically/geographically).

  • Graph Data Mining with Arabesque
    Eslam Hussein, Abdurrahman Ghanem, Vinicius Vitor dos Santos Dias, Carlos HC Teixeira, Ghadeer AbuOda, Marco Serafini, Georgos Siganos, Gianmarco De Francisci Morales, Ashraf Aboulnaga and Mohammed Zaki. In Proceedings of the 2017 ACM International Conference on Management of Data (SIGMOD'17). Pages 1647–1650.. 2017.
    • Nature Inspired Algorithms for Solving the Community Detection Problem
      Eslam Hussein, Ahmed Ibrahem Hafez, Aboul Ella Hassanien and Aly A Fahmy. In Logic Journal of the IGPL, 25(6) Pages 902–914.. 2017.
      • A Discrete Bat Algorithm for the Community Detection Problem
        Eslam Hussein, Ahmed Ibrahem Hafez, Aboul Ella Hassanien and Aly A Fahmy. In 10th International Conference Hybrid Artificial Intelligent Systems. Pages 188–199.. 2015.
        • Community Detection Algorithm based on Artificial Fish Swarm Optimization
          Eslam Hussein, Ahmed Ibrahem Hafez, Aboul Ella Hassanien and Aly A Fahmy. In Intelligent Systems'2014. Pages 509–521.. 2015.
          • Blog Clustering with Committee Approach
            Fatma H Ismail, Eslam Hussein, Aboul Ella Hassanien and Tai-Hoon Kim. In Fourth International Conference on Information Science and Industrial Applications (ISI). . 2015.