My name is Alex Leavitt, and I'm a social scientist and internet researcher. I currently work for Facebook Research, and I reside in San Francisco, after living in Los Angeles, Kyoto, and Boston.
Previously, I worked with danah boyd at Microsoft Research New England. Before that, I was a researcher in the Massachusetts Institute of Technology's Comparative Media Studies department, where I worked on the Convergence Culture Consortium project.
I frequently work across industry and academia, publishing my research in venues like ACM CSCW (Conference on Computer-Supported Cooperative Work and Social Computing) and ACM SIGCHI (Special Interest Group on Computer-Human Interaction). Spanning my research career, I have been part of a number of data science and user experience research teams with a handful of major media and analytics companies, like Facebook, Sony PlayStation, Disney Interactive, and SocialFlow.
Numerous outlets have also featured my research, such as the New York Times, the Wall Street Journal, Bloomberg, CNN, and the Huffington Post.
You can also read some of my non-peer-reviewed writing:
My research focuses on participation in and across networked technologies, specifically social media platforms and online games. I am particularly interested in how online platforms facilitate user-generated content production, social network formation, information sharing practices, and group collaboration.
In my work, I combine traditional ethnography with computational social science to investigate social traces in online social systems. I like to pursue mixed methods research involving both interpretive and analytical approaches, and I am testing new methodologies for using digital data to look at technological affordances and emergent technosocial behaviors. Recently, I have been experimenting with data processing involving social network analysis, machine learning, and natural language processing using high performance computational resources.
In my current role at Facebook, I am a member of the User Experience Research group, where I work with the News Feed product team.
For my dissertation, I studied how people collaborate to aggregate information about ongoing news events. Specifically, I looked at how crowds and algorithms affect the information dynamics of breaking news reporting on reddit. Using digital trace ethnography and large-scale computational analysis, I explored the social and technical aspects of peer production in rapid information aggregation by conducting over 50 interviews with users, moderators, and administrators, which I situated in a historical dataset of 2 billion messages posted to the site. My research questions focused on how voting, ranking, visibility, and moderation affect what kind of collaborations occur in high-tempo news events.
You can now download a full copy of my dissertation, Upvoting the News: Breaking News Aggregation, Crowd Collaboration, and Algorithm-Driven Attention on reddit.com. [PDF]
Or, if you need to quickly figure out why we should care about this topic, feel free to read a short primer that I wrote before starting my dissertation: Upvoting the News: Reddit’s potential role in breaking news coverage.