Shadi Shajari Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
unknown
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Shadi Shajari's research focuses on the analysis and detection of anomalous behaviors within online platforms, particularly on YouTube. Their work investigates methods for characterizing commenter activities and developing frameworks to safeguard discussions by identifying suspicious or unusual engagement patterns. This research has resulted in several publications exploring network-centric approaches and graph-based techniques, such as Graph2Vec, for detecting these anomalies. Shajari has collaborated with researchers at the University of Arkansas at Little Rock, including Mustafa Alassad, Nitin Agarwal, and Ridwan Amure, contributing to a shared body of work in this area. The researcher's h-index is 3, with 8 publications and 35 citations.
Metrics
- h-index: 4
- Publications: 8
- Citations: 40
Selected Publications
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Developing a Commenter Behavior-Based Framework for Characterizing YouTube Channels (2026)
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Navigating the Anomalies: A Comprehensive Analysis of YouTube Channel Behavior (2025)
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Detecting and Measuring Anomalous Behaviors on YouTube (2025)
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Safeguarding youtube discussions: a framework for detecting anomalous commenter and engagement behaviors (2025)
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Developing a network-centric approach for anomalous behavior detection on youtube (2025)
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Characterizing Suspicious Commenter Behaviors (2023)
Collaboration Network
Top Collaborators
- Characterizing Suspicious Commenter Behaviors
- Developing a network-centric approach for anomalous behavior detection on youtube
- Safeguarding youtube discussions: a framework for detecting anomalous commenter and engagement behaviors
- Detecting and Measuring Anomalous Behaviors on YouTube
- Detecting Suspicious Commenter Mob Behaviors on YouTube Using Graph2Vec
- Characterizing Suspicious Commenter Behaviors
- Commenter Behavior Characterization on YouTube Channels
- Detecting Suspicious Commenter Mob Behaviors on YouTube Using Graph2Vec
- Detecting and Measuring Anomalous Behaviors on YouTube
- Navigating the Anomalies: A Comprehensive Analysis of YouTube Channel Behavior
- Commenter Behavior Characterization on YouTube Channels
- Navigating the Anomalies: A Comprehensive Analysis of YouTube Channel Behavior
- Developing a Commenter Behavior-Based Framework for Characterizing YouTube Channels
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