Joseph Kready Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
Research Areas
Biography and Research Information
OverviewAI-generated summary
Joseph Kready's research investigates the propagation and influence of digital content, particularly focusing on bias within online platforms and the spread of toxicity. His work has examined the characteristics of video recommendation systems on platforms like YouTube, exploring how cross-lingual and cross-topical contexts affect these algorithms. Kready has also studied the reach and influence of digital activities associated with far-right actors across various social media environments, comparing mainstream platforms with those emphasizing 'free speech.'
Additionally, his research applies epidemiological models to understand the dissemination of harmful content, such as toxicity related to COVID-19 on Twitter. These studies highlight Kready's interest in the dynamics of online communication, the impact of algorithms, and the spread of information and misinformation in digital spaces. He has collaborated with researchers from the University of Arkansas at Little Rock and Southern Arkansas University on these topics.
Metrics
- h-index: 5
- Publications: 5
- Citations: 84
Selected Publications
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Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms (2022)
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Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context (2021)
Collaboration Network
Top Collaborators
- Examining Video Recommendation Bias on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Applying an Epidemiological Model to Evaluate the Propagation of Toxicity related to COVID-19 on Twitter
- Examining Video Recommendation Bias on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Examining Video Recommendation Bias on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Examining Video Recommendation Bias on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Applying an Epidemiological Model to Evaluate the Propagation of Toxicity related to COVID-19 on Twitter
- Applying an Epidemiological Model to Evaluate the Propagation of Toxicity related to COVID-19 on Twitter
- Applying an Epidemiological Model to Evaluate the Propagation of Toxicity related to COVID-19 on Twitter
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
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