Esther L. Mead
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.
Assistant Professor of Information Systems and Data Science / Business Graduate Director
Also affiliated: University of Arkansas System (2022)
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Esther Mead's research focuses on the propagation and regulation of online discourse, particularly concerning misinformation and toxicity on social media platforms like YouTube and Twitter. Her work employs computational and epidemiological modeling approaches to analyze how information, both legitimate and harmful, spreads within digital environments. Mead has investigated the mechanisms behind video recommendation bias on YouTube and examined the influence of digital activity among far-right actors on various social media platforms.
Her publications also address the application of diffusion of innovations theory to understand adoption stages in connective action campaigns. Mead has utilized epidemiological models to study the spread of misinformation during social movements such as Black Lives Matter, as well as the propagation of toxicity and legitimate information related to COVID-19 on Twitter. She has collaborated with researchers from the University of Arkansas at Little Rock on multiple publications.
Metrics
- h-index: 9
- Publications: 26
- Citations: 315
Positions
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Assistant Professor of Information Systems and Data Science / Business Graduate Director publications 2023–2024Southern Arkansas University Institution web page
Selected Publications
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Text Mining Domestic Extremism Topics on Multiple Social Media Platforms (2024)
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Proposing Location-based Predictive Features for Modeling Refugee Counts (2023)
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Developing Approaches to Detect and Mitigate COVID-19 Misinfodemic in Social Networks for Proactive Policymaking (2022)
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Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns (2022)
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Surface Web vs Deep Web vs Dark Web (2022)
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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)
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Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter (2021)
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Using Diffusion of Innovations Theory to Study Connective Action Campaigns (2021)
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Proposing a Broader Scope of Predictive Features for Modeling Refugee Counts (2021)
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Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube (2021)
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A public online resource to track COVID-19 misinfodemic (2021)
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Surface Web vs Deep Web vs Dark Web (2020)
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The Ebb and flow of the COVID-19 misinformation themes (2020)
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Developing an Epidemiological Model to Study Spread of Toxicity on YouTube (2020)
Collaboration Network
Top Collaborators
- Identifying Toxicity Within YouTube Video Comment
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Developing an Epidemiological Model to Study Spread of Toxicity on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
Showing 5 of 15 shared publications
- Developing an Epidemiological Model to Study Spread of Toxicity on YouTube
- Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter
- Proposing a Broader Scope of Predictive Features for Modeling Refugee Counts
- Proposing Location-based Predictive Features for Modeling Refugee Counts
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- A public online resource to track COVID-19 misinfodemic
- The Ebb and flow of the COVID-19 misinformation themes
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Using Diffusion of Innovations Theory to Study Connective Action Campaigns
- Developing Approaches to Detect and Mitigate COVID-19 Misinfodemic in Social Networks for Proactive Policymaking
- Identifying Toxicity Within YouTube Video Comment
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Developing an Epidemiological Model to Study Spread of Toxicity on YouTube
- Identifying Toxicity Within YouTube Video Comment
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Using Diffusion of Innovations Theory to Study Connective Action Campaigns
- Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter
- Using Diffusion of Innovations Theory to Study Connective Action Campaigns
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Using Diffusion of Innovations Theory to Study Connective Action Campaigns
- Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter
- Proposing Location-based Predictive Features for Modeling Refugee Counts
- 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
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Text Mining Domestic Extremism Topics on Multiple Social Media Platforms
- Teamwork skill assessment: Development of a measure for academia
- A public online resource to track COVID-19 misinfodemic
- A public online resource to track COVID-19 misinfodemic
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