Esther Mead Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

Southern Arkansas University

faculty

9 h-index 25 pubs 296 cited

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Biography and Research Information

OverviewAI-generated summary

Esther Mead's research investigates the propagation and regulation of online discourse, particularly focusing on toxicity and misinformation across social media platforms. Her work employs computational and epidemiological models to analyze the spread of information and harmful content on platforms such as YouTube and Twitter. Mead has studied the mechanisms behind video recommendation bias on YouTube and examined how diffusion of innovations theory can explain the adoption stages in connective action campaigns.

Her publications also address the spread of legitimate information alongside misinformation, specifically in the context of events like the Black Lives Matter movement and the COVID-19 pandemic. Mead has further assessed the influence of digital activity from far-right actors on both mainstream and alternative social media platforms. She has a notable record of collaboration, with nine shared publications with Nitin Agarwal and multiple shared publications with Thomas Marcoux, Joseph Kready, and Billy Spann, primarily from the University of Arkansas at Little Rock.

Metrics

  • h-index: 9
  • Publications: 25
  • Citations: 296

Selected Publications

  • Text Mining Domestic Extremism Topics on Multiple Social Media Platforms (2024) DOI
  • Proposing Location-based Predictive Features for Modeling Refugee Counts (2023) DOI
  • Developing Approaches to Detect and Mitigate COVID-19 Misinfodemic in Social Networks for Proactive Policymaking (2022) DOI
  • Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns (2022) DOI
  • Surface Web vs Deep Web vs Dark Web (2022) DOI
  • Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms (2022) DOI
  • Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context (2021) DOI
  • Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter (2021) DOI
  • Using Diffusion of Innovations Theory to Study Connective Action Campaigns (2021) DOI
  • Proposing a Broader Scope of Predictive Features for Modeling Refugee Counts (2021) DOI
  • Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube (2021) DOI
  • A public online resource to track COVID-19 misinfodemic (2021) DOI

Collaborators

Researchers in the database who share publications

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