Scholar
Thomas R Davidson
Google Scholar ID: kbn94xgAAAAJ
Assistant Professor of Sociology, Rutgers University
Citations & Impact
Citations
5,301
H-index
12
i10-index
15
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- 1. Published an article in Mobilization, arguing that algorithmic feedback loops enable social movement actors to generate and sustain attention from online audiences.
- 2. Published an article in Political Communication, showing that populist parties in Europe have attracted more engagement on Facebook than other parties and that their online advantages appear to be growing.
- 3. Contributed a chapter to the Oxford Handbook on the Sociology of Machine Learning, providing an overview of research on hate speech detection and identifying several directions for further inquiry.
- 4. Received a Foundational Integrity Research award from Meta to conduct experimental research on how social context influences judgments about whether certain content is hateful or abusive.
- 5. A forthcoming paper in Nature Human Behaviour compares parallel experiments with human subjects and vision language models, demonstrating how AI can make context-sensitive moderation decisions that align with human judgment.
Research Experience
- 1. Researching social media, populism, and far-right activism.
- 2. Studying how algorithmic feedback loops enable social movement actors to generate and sustain attention from online audiences.
- 3. Investigating how populist parties in Europe have attracted more engagement on Facebook than other parties, and that their online advantages appear to be growing.
- 4. Currently working on projects related to (i) how the COVID-19 pandemic led to a surge in support for right-wing populists in Europe; (ii) how political parties adapted their language in response to changing conditions during the Syrian refugee crisis; and (iii) using simulations to understand the impacts of algorithmic ranking and recommendation on online activism.
- 5. Focusing on identifying and understanding hate speech on social media, including early work on distinguishing hate speech from other forms of offensive language, and later research on racial bias in hate speech and abusive language detection systems.
Background
- He is an Assistant Professor of Sociology at Rutgers University—New Brunswick. He specializes in using computational methods and data from social media to study far-right activism, populism, and hate speech. Recently, he has been working on several papers exploring the methodological applications of generative artificial intelligence.
Co-authors