Skip to content

Seminar series

Digital politics and foreign interventions

A natural language processing approach

Add to calendar 2024-02-21 16:30 2024-02-21 17:30 Europe/Rome Digital politics and foreign interventions Online meeting Zoom YYYY-MM-DD


21 February 2024

16:30 - 17:30 CET


Online meeting


In the context of the CIVICA Data Science seminar series, this session features a presentation by Ashrakat Elshehawy (postdoctoral fellow at Stanford's King Center on Global Development).

Foreign entities employing targeted political messaging to influence the politics of another nation is now more straightforward and common than before. Disinformation campaigns do not solely aim to transmit deceitful political information to other countries, but they also aim at changing attitudes regarding scientific findings, governance, and democratic institutions. Powerful non-democratic states have both the means and the incentive to spread such discourse to democratic and undemocratic countries. The main aim of the talk is to uncover a research agenda emphasising ways in which foreign-owned media employ illiberal discourse abroad in democratic and undemocratic regimes, as well as its timing relative to the calendar of significant political events in the receiving countries (e.g. Elshehawy et. al 2022). The talk also focuses on providing an overview of how to retrieve and use corpora of over a million news stories of state-sponsored communication, it also provides insights on which tools of Natural Language Processing are helpful for such tasks; mainly in detecting foreign propaganda and its strategic use in affecting the domestic politics of receiving countries.

About the series:

The CIVICA Data Science seminar series is the interdisciplinary forum of the CIVICA European University of Social Sciences, and alliance of eight leading higher education and research institutions. We foster a community of researchers, practitioners, and policymakers working to address complex societal challenges through the use of novel methodological and data-driven approaches, drawing from machine learning and quantitative methods from biology, sociology, political sciences, economics, and physics, among other disciplines. Shared among the partner institutions of the CIVICA network, this series directly addresses the data science research stream of the CIVICA initiative. Register here.

Go back to top of the page