Current Research

I work at the intersection between Social Science and Computer Science. Recent advances in collecting and analysing human data are revolutionising the way in which we can do research about societies, and I am really excited about these opportunities.

PhD Students

I currently accept applications for PhD supervision from students eager to work at the intersection between computer science and social science. If you are interested, please do get in touch, ideally already with a great idea and a first sketch of a proposal. At the moment I already work with a group of greatly talented researchers.

Andreas Küpfer (TU Darmstadt)

Eira Jepson (Cardiff University)

The Lab

This is what is going on in the lab at the moment.

1 Text-as-Data

How Presidents Answer the Call of International Capital: In this work with David Doyle, Nina Wiesehomeier, we show how Latin American Presidents use their state-of-the-union speeches to strategically communicate with International Captial Markets. [paper]

New Research Methods for the Analysis of Party Pledges

In the MiMac project I collaborate with ten colleagues from six international universities to investigate parties’ electoral pledges during election campaigns. As an interdisciplinary team of Computational Linguists and Social Scientist—led by Elin Naurin (Gothenburg) and Robert Thomson (Monash), and funded by the Swedish Riksbankens Jubileumsfond with € 1.15 million—we are developing AI-powered tools will enable researchers to examine parties’ campaign promises in large amounts of text and speech.

Together with Jac Larner and Fraser McMillan we are collecting and annotating the electoral pledges from Wales’ parties. Using and refining these new NLP tools, we are testing theories about devolved politics and single-party systems.

In our working paper “Psychological Distance and Event Construal Depend Not Only on Event Distance, but Also on Event Resolution.” (with Hannah Bechara and Slava Jankin) we use lab experiments and a corpus of NYT articles on the US presidential elections. The article lays the necessary groundwork for another paper: the Politics of Psychological Distance. What drives psychological distance is not only the event distance, i.e. how far an event is away. Both the event distance and the event resolution jointly determine individuals’ psychological distance to an event, and with it the event construal and important behavioral downstream e ffects such as planning for a particular event.

2 Synthetic Data

Really Useful Synthetic Data — Promises and Challenges of Releasing Sensitive Information With Differentially Private Data Synthesizers: Marcel Neunhoeffer and I develop a framework to measure the utility of differentially private synthetic data. [paper]

3 Images-as-Data

Detecting Election Irregularities with Machine Learning for Visual Data

This is a larger project together with Michelle Brown (NDI), J. Andrew Harris (NYU AD) and Zach Warner (Purdue) where we use computer vision to detect the presence of irregularities in election results. Funded by the ESRC, we are collaborating with the National Democratic Institute to improve electoral integrity in fragile democracies all around the world.