About Me

I study politicians, non-profit organizations, and television fans to understand how people use social media to organize, discuss, and enact social change. 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.

Social media has some very real toxicity challenges, like harassment and cyberbullying, that diminish its utility for collective and democratic efforts, so I work on curbing those too (Belfer Fellowship, Mozilla Grant, Nayar Prize).

I have a few titles at the University of Michigan:

• Director, Resource Center for Minority Data, ICPSR
• Research Associate Professor, Institute for Social Research
• Associate Professor, School of Information

From 2010 - 2017, I was a faculty member in the Humanities Department and directed the Collective Action and Social Media Lab at Illinois Institute of Technology.

Work with Me

Post Docs

I’m hiring a faculty research fellow. The Fellow will join a team of researchers from ICPSR and the University of Michigan School of Information (UMSI) working to understand the impacts of data archiving and sharing in social science. The position is funded by a grant from the National Science Foundation to (1) understand how to responsibly allocate resources to data archiving so that we can (2) articulate data archiving policies that efficiently and effectively achieve innovation and transparency in social science.

The project will construct two measures of data’s scholarly impact—secondary impact and diversity—that depend on citations of the data. The ICPSR Bibliography of Data-Related Literature (the “Bibliography”) links over 80,000 research publications to the ICPSR data on which they are based. Generating the bibliography for a given study is currently a manual process, and datasets are often cited informally. The focus of the fellowship will be developing a predictive model that can assist staff in identifying informal and incomplete data citations. Given a set of publications, the model will (1) identify informal or incomplete dataset references and (2) determine whether the datasets match any in ICPSR’s collection.

Apply through Interfolio; review of applications beings September 1, 2019 and will continue until the position is filled.

PhD Students

I’m recruiting PhD students for fall 2020. 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. I’m looking for 1-2 PhD students who are interested in

• digital curation and data management, especially administrative and/or social media data
• politics and social media, especially in the U.S. and/or the Global South

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.

For instance, one of the papers I’m writing now uses a classification model we developed in Python using scikit-learn and nltk. We label tweets with that model and then use multinomial logisitic regression to understand differences between policy tweeting patterns in Congress. I use this approach—build and train a model, label some content, analyze the patterns, and explain the implications for political science and communication—in most of my work, and you should be interested in those steps and experienced in at least one of them.

Undergraduates

I welcome undergrads in my research group! Right now, the best way to get involved is through the Undergraduate Research Opportunity Program (UROP) at Michigan. I’ll start interviewing for Fall/Winter on September 11, 2019. This year’s project is called “Using Machine Learning and Experiments to Detect and Address Extremism”:

Extremist groups are especially adept at hiding in plain sight by using language that differs only slightly from acceptable speech (e.g., “blame on both sides”) or employing thinly-veiled phrases that mask nefarious intent (e.g., “preserve our culture”). The subtleties of white supremacist language, especially, are not effectively captured by existing computational approaches to detecting and addressing it online. This project attempts to address this challenge by building an adaptive language model to detect white supremacist speech online. We will build machine learning models that can detect extremist speech and its changes (either over time or from innocuous speech) and create an API to help partners and users rate content they encounter.

Current Funded Research Projects

• Measuring and Improving the Efficacy of Curation Activities in Data Archives
• Developing Evidence-based Data Sharing and Archiving Policies
• Belfer Fellowship at ADL’s Center for Technology and Society
• Learning and Automating De-escalation Strategies in Online Discussions
• Data Science in the Public Sector
• Open Badges for Researcher Credentialing

Get in Touch

Email is best.

Publications

Here’s a PDF of my CV, and a few recent publications:

• Hemphill, L., and Schöpke-Gonzalez, A.M. (2020) Two Computational Models for Analyzing Political Attention in Social Media. Accepted for publication at the International AAAI Conference on Web and Social Media (ICWSM 2020).
• 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
• 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.
• 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
• Hemphill, L., Roback, A. (2014) Tweet Acts: How Constituents Lobby Congress via Twitter. Proceedings of the 2014 ACM Conference on Computer Supported Cooperative Work, Baltimore, MD. doi: 10.1145/2531602.2531735
• Hemphill, L., Otterbacher, J., and Shapiro, M.A. (2013) What’s Congress Doing on Twitter? Proceedings of the 2013 ACM Conference on Computer Supported Cooperative Work, San Antonio, TX, 887-886. doi: 10.1145/2441776.2441876

Working Papers

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.

• Im, J., Chandrasekharan, E., Sargent, J., Lighthammer, P., Denby, T., Bhargava, A., Hemphill, L., Jurgens, D., and Gilbert, E. (2019) Still out there: Modeling and Identifying Russian Troll Accounts on Twitter
• Hemphill, L., Million, A.J., and Erickson, I. (2018) Crafting Moral Infrastructures: How Non-profits Use Facebook to Survive
• 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)