Obianuju Okeke Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
University of Arkansas at Little Rock
unknown
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Biography and Research Information
OverviewAI-generated summary
Obianuju Okeke's research investigates bias and fairness within artificial intelligence, particularly focusing on YouTube's recommendation algorithms. Her work examines how these systems can perpetuate biases related to emotion, morality, and geopolitical discourse, with specific attention to content concerning China and the Uyghur population. Okeke also studies the emergence of collective identity through socio-computational techniques and the application of parallel processing for efficient transcript generation in multimedia environments. She has authored five publications and has an h-index of 3, with 36 total citations. Okeke collaborates with several researchers at the University of Arkansas at Little Rock, including Billy Spann, Mert Can Çakmak, Nitin Agarwal, and Ugochukwu Onyepunuka, with whom she shares multiple publications.
Metrics
- h-index: 3
- Publications: 5
- Citations: 36
Selected Publications
- Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content (2024) DOI
- Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm (2023) DOI
- Adopting Parallel Processing for Rapid Generation of Transcripts in Multimedia-rich Online Information Environment (2023) DOI
- Evaluating the Emergence of Collective Identity using Socio-Computational Techniques (2023) DOI
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