Democratically healthy news recommendation: aligning NLP with society, theory, and evaluation

December 4, 2023, 2:00 p.m. (CET)

Colloquium for Computational Linguistics and Linguistics in Stuttgart

Time: December 4, 2023, 2:00 p.m. – 4:00 p.m.
Lecturer: Myrthe Reuver
Meeting mode: hybrid
Venue: V5.01 on the ground floor
Pfaffenwaldring 5 b
70569  Stuttgart
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Democratically healthy news recommendation: aligning NLP with society, theory, and evaluation
News recommender systems provide news article recommendations based on a user's interests and clicks. This personalization could harm democratic societies: citizens may be unaware of information beyond their own interests, leading to filter bubbles and a lack of shared public debate. A healthy collective information environment may require more diversity in recommendations, such as recommending different viewpoints on societal debates. Natural Language Processing could play a role in providing more diverse recommendations, but solving such a complex societal problem requires several key ingredients. These include interdisciplinary collaboration with experts on democracy, careful reflection on the suitability of existing NLP tasks and models, and data that is connected to relevant social science theory. Additionally, evaluation is essential: do we measure what we intend to measure, and is our NLP model actually improving recommendations in terms of our democratic values? I will discuss my PhD projects and findings - which include the lack of cross-topic robustness of stance detection models, and evaluation of models beyond predictive validity - and relate these to how we can tackle the problem of non-diverse news recommendation, and similar complex societal research questions.

Myrthe Reuver is a 4th year PhD candidate in the Computational Linguistics and Text Mining Lab (CLTL) at the Vrije Universiteit Amsterdam, with advisors prof.dr. Antske Fokkens (CLTL) and prof.dr. Suzan Verberne (Leiden University). Myrthe’s PhD is on analyzing diversity in news recommender systems, and her research has focussed on computational argumentation, precise evaluation, and interdisciplinary collaboration with social scientists and philosophers. Aside from her research papers, Myrthe has also applied NLP research during a summer internship at LinkedIn in Dublin, and has been featured in Dutch national newspapers about responsible use of AI.

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