S. Dağtaş
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: Philips (Finland) (2003); Purdue University West Lafayette (2002); Systems, Applications & Products in Data Processing (Canada) (2007); Philips (United States) (2000–2003); IPS Research (United States) (2000–2002); Arkansas Department of Agriculture (2006)
Faculty Researcher
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
S. Dağtaş investigates user behavior and bias within online media platforms, with a particular focus on YouTube Shorts and Reddit. Their recent work includes simulating user watch-time to analyze recommendation algorithms and modeling the propagation of toxicity on social media platforms like Reddit, drawing parallels to epidemiological patterns. Dağtaş collaborates with researchers at the University of Arkansas at Little Rock, including Mert Can Çakmak, Nitin Agarwal, and Diwash Poudel, on shared publications.
With an h-index of 9 and 489 total citations across 15 publications, Dağtaş's research contributes to the understanding of digital media dynamics and their societal impacts. Their most recent publication is from 2026, indicating ongoing activity in the field.
Metrics
- h-index: 9
- Publications: 15
- Citations: 490
Selected Publications
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Simulating User Watch-Time to Investigate Bias in YouTube Shorts Recommendations (2026)
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Modeling Toxicity Propagation on Reddit Using Epidemiology (2025)
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Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics (2024)
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Real-Time and Secure Wireless Health Monitoring (2008)
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Multi-Stage Real Time Health Monitoring via ZigBee in Smart Homes (2007)
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New Set of Algorithms to Create 3D Images of Cellular Structures using Light Microscopy (2006)
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A Multi-Modal Virtual Environment with Text-Independent Real-Time Speaker Identification (2005)
Collaboration Network
Top Collaborators
- Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics
- Simulating User Watch-Time to Investigate Bias in YouTube Shorts Recommendations
- Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics
- Modeling Toxicity Propagation on Reddit Using Epidemiology
- Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics
- Modeling Toxicity Propagation on Reddit Using Epidemiology
- Simulating User Watch-Time to Investigate Bias in YouTube Shorts Recommendations
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