280 citations · 472 across the 14 of their papers we have counts for
14 papers
Deep Learning for Political Science
Kakia Chatsiou, Slava Jankin Mikhaylov
Political science, and social science in general, have traditionally been using computational methods to study areas such as voting behavior, policy making, international conflict,…
Artificial Intelligence for the Public Sector: Opportunities and challenges of cross-sector collaboration
Slava Jankin Mikhaylov, Marc Esteve, Averill Campion
Public sector organisations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertain…
Transfer Topic Labeling with Domain-Specific Knowledge Base: An Analysis of UK House of Commons Speeches 1935-2014
Alexander Herzog, Peter John, Slava Jankin Mikhaylov
Topic models are widely used in natural language processing, allowing researchers to estimate the underlying themes in a collection of documents. Most topic models use unsupervised…
Multiplex Communities and the Emergence of International Conflict
Caleb Pomeroy, Niheer Dasandi, Slava Jankin Mikhaylov
Advances in community detection reveal new insights into multiplex and multilayer networks. Less work, however, investigates the relationship between these communities and outcomes…
Disunited Nations? A Multiplex Network Approach to Detecting Preference Affinity Blocs using Texts and Votes
Caleb Pomeroy, Niheer Dasandi, Slava J. Mikhaylov
This paper contributes to an emerging literature that models votes and text in tandem to better understand polarization of expressed preferences. It introduces a new approach to es…
Learning to Predict with Highly Granular Temporal Data: Estimating individual behavioral profiles with smart meter data
Anastasia Ushakova, Slava J. Mikhaylov
Big spatio-temporal datasets, available through both open and administrative data sources, offer significant potential for social science research. The magnitude of the data allows…