- 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.
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