Tom Davidson's personal webpage





About me

I’m a PhD candidate in the Department of Sociology at Cornell University. I'm supervised by Mabel Berezin, Filiz Garip, and Michael Macy (chair). I’m a member of the Social Dynamics Lab. I study politics, culture, and social structures using computational social science methodologies including social network analysis, machine learning, and natural language processing.


I am working on a dissertation studying the online interactions between social movements, political parties, and their supporters in the United Kingdom. I use digital trace data to uncover relationships between extremist movements and mainstream parties that are otherwise hidden and analyze how these relationships impact both groups. I am also studying the network of actors involved in the Brexit referendum debate online and the interactions between them, showing how the Leave campaign amassed a far larger following in the run up to the vote and how the vast majority of users appeared to hold negative opinions of the E.U. I recently wrote a blog post about the role of social media 2017 UK General Election and co-authored an article in the Washington Post's The Monkey Cage blog on the 2017 German election.

A second line of work focuses on identifying and understanding hate speech and hate speakers on social media using natural language processing and machine learning. You can read our ICWSM paper on automated hate speech detection here and download our data and model here. Our work has been covered in Wired Magazine, Tech Republic, and New Scientist. We also wrote a paper focusing on the commonalities between hate speech detection and other topics, including online abuse and cyberbullying, for the Association for Computational Linguistics 1st Workshop of Abusive Language Online. You can read the article in the workshop proceedings.

I have also collaborated with Paromita Sanyal at FSU to study the impact of microcredit participation on women's social networks in rural India. We find that participation in associations allows women to expand their personal networks and enhance their social capital. Our work was recently published in Social Forces.

Data science

In addition to my academic research I have also been learning about how data science can be used to directly address real world problems in the public sphere and in industry.

In the summer of 2016 I was an Eric and Wendy Schmidt Data Science for Social Good Fellow at the University of Chicago. I worked on a project using machine learning to improve an early-warning system to identify police misconduct and helped develop a new model to predict risks at the dispatch level. You can read about our work here, along with media coverage in The Chicago Tribune, NPR, Mother Jones, the Economist, and Forbes. As of spring 2017 our system is being implemented into two police departments, you can read about the progress here.

In 2017 I was worked as a summer intern in the Data Science Research & Development department at Civis Analytics in Chicago, where I used natural language processing and and machine learning to help build a tool to monitor political discussion on Twitter. In summer 2018 I was a Core Data Science intern at Facebook in Menlo Park. I helped to evaluate and deploy new tools to help in on-going election integrity efforts.


Please feel free to get in touch at trd54 at cornell dot edu.