Social media has some very real toxicity challenges, like harassment and cyberbullying, that diminish its utility for collective and democratic efforts, and I study human-AI content moderation to address those challenges (NSF Grant, Belfer Fellowship, Mozilla Grant, Nayar Prize). I also study data curation, especially how we evaluate (a) the impacts of data reuse and (b) investments in curating and disseminating research data. My work has been funded by the National Science Foundation, the Institute for Museum and Library Services, the Nayar Prize, Mozilla, the Anti-Defamation League, Amazon, and DiscoverText.
I have a few titles at the University of Michigan:
Work with Me
Thank you for your interest! I’m not recruiting students or postdocs in the next 6 months (at least).
I’m not sure whether I’m recruiting PhD students for fall 2023. Check out some of my research, and contact me if you’re interested.
PhD students will be admitted through the School of Information; applications are due December 1. Here are some of the questions I’m working on:
- How should we structure archives of dynamic social media data?
- How can data recommender systems impact research data reuse?
- How can we make social media content moderation systems more productive and inclusive?
I’m especially interested in students who are curious about the impact of social media on democracy and civic engagement and how we can use computation and automation to make conversations and participation (in politics, in science, in society) more just and accessible. You should have stats and computational expertise or be willing to gain some quickly. You should also have expertise or a strong interest in political science, critical race and feminism studies, and/or communication.
Current Funded Research Projects
Get in Touch
Email is best.
Here’s a PDF of my CV and some recent publications:
Social Media, Content Moderation, and Extremism
- Hemphill, L. (2022) Very Fine People: What Social Media Platforms Miss About White Supremacist Speech. The Anti-Defamation League.
- Balasubramanian, S.K., Bilgic, M., Culotta, A., Hemphill, L., Nikolich, A., Shapiro, M.A., (2022) Leaders or Followers? A Temporal Analysis of Tweets from IRA Trolls. 16th International AAAI Conference on Web and Social Media (ICWSM 2022).
- Hemphill, L., Million, A. J., & Erickson, I. (2021). How nonprofits use Facebook to craft infrastructure. First Monday. https://doi.org/10.5210/fm.v26i3.10265
- Im, J., Chandrasekharan, E., Sargent, J., Lighthammer, P., Denby, T., Bhargava, A., Hemphill, L., Jurgens, D., & Gilbert, E. (2020). Still out there: Modeling and Identifying Russian Troll Accounts on Twitter. 12th ACM Conference on Web Science, 1–10. https://doi.org/10.1145/3394231.3397889 (* Best Paper Runner-up)
- Jurgens, D., Chandrasekharan, E., and Hemphill, L. (2019) A Just and Comprehensive Strategy for Using NLP to Address Online Abuse. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019). Florence, Italy.
- Liu, P., Guberman, J., Hemphill, L., & Culotta, A. (2018). Forecasting the presence and intensity of hostility on Instagram using linguistic and social features. In Proceedings of the 12th International Conference on Web and Social Media. Stanford, CA, USA.
Data Curation and Archiving
- Hemphill, L., Pienta, A., Lafia, S., Akmon, D., and Bleckley, D. (2022) How do Properties of Data, Their Curation, and Their Funding Relate to Reuse?) Journal of the Association for Information Science and Technology. doi: 10.1002/asi.24646.
- Lafia, S., Thomer, A., Bleckley, D., Akmon, D., & Hemphill, L. (2021). Leveraging Machine Learning to Detect Data Curation Activities. Proceedings of 2021 IEEE 17th International Conference on E-Science. http://arxiv.org/abs/2105.00030
- Hemphill, L., Hedstrom, M. L., & Leonard, S. H. (2020). Saving social media data: Understanding data management practices among social media researchers and their implications for archives. Journal of the Association for Information Science and Technology, 3, 34. https://doi.org/10.1002/asi.24368
- Hemphill, L., Russell, A., & Schöpke-Gonzalez, A. M. (2020). What Drives U.S. Congressional Members’ Policy Attention on Twitter? Policy & Internet. https://doi.org/10.1002/poi3.245
- Hemphill, L., and Schöpke-Gonzalez, A.M. (2020) Two Computational Models for Analyzing Political Attention in Social Media. International AAAI Conference on Web and Social Media (ICWSM 2020), 260-271.
- Hemphill, L. and Shapiro, M.A. (2019) Appealing to the Base or to the Moveable Middle? Incumbents’ Partisan Messaging Before the 2016 U.S. Congressional Elections. Journal of Information Technology and Politics. doi: 10.1080/19331681.2019.1651685
- Shapiro, M.A. and Hemphill, L. (2017). Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content? Policy and Internet . doi: 10.1002/poi3.120
- Hemphill, L., Culotta, A., & Heston, M. (2016). #Polar Scores: Measuring Partisanship Using Social Media Content. Journal of Information Technology & Politics. 13(4). doi: 10.1080/19331681.2016.1214093
Some of my work that’s not (yet) published. These are workshop papers, papers under review, and/or longer versions of papers for conferences that review only abstracts during submission.
- Lafia, S., Ko, J-W., Moss, E., Kim, J., Thomer, A., Hemphill, L. (2021) Detecting Informal Data References in Academic Literature.
- Hemphill, L., Leonard, S.H., and Hedstrom, M. (2018) Developing a Social Media Archive at ICPSR
- Hemphill, L. (2018) More Specificity, More Attention to Social Context: Reframing How We Address ‘‘Bad Actors’’
- Hemphill, L., Culotta, A., and Heston, M. (2013) Framing in Social Media: How the US Congress Uses Twitter Hashtags to Frame Political Issues
You can find more at
- Deep Blue (Michigan’s institutional repository)
- arXiv.org (open access e-prints)
- SSRN (though I won’t post new papers here now that Elsevier owns it)