Linked Multi-Modal Data on Russian Domestic and Foreign Policy Speeches

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Authors: Daria Blinova, Gayathri Emuru, Rakesh Emuru, Kushagradheer Shridheer Srivastava, Mina Rulis, Sunita Chandrasekaran, Benjamin E. Bagozzi
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Abstract

This Dataverse entry incldues a dataset of interlinked multimodal political communications from the Russian government, addressing persistent deficiencies in the availability of social text- and image-based data for authoritarian politics contexts. The dataset comprises two large corpora of official speeches delivered by senior actors within the Kremlin and the Russian Ministry of Foreign Affairs over multiple decades. For each speech, we provide Russian- and English-language texts, associated images and captions where available, and harmonized metadata including (e.g.) dates, speakers, (geo)locations, and official government content tags. Unique identifiers link images to speeches and align Russian and English versions of the same communication texts. We further augment these linked datasets with validated topical annotations for both speech texts and speech images, which are generated via transformer-based multimodal topic modeling and refined by a Russian politics expert. The resulting data resources support multimodal, multilingual, temporal, and/or spatial analyses of (authoritarian) political communication and offer a valuable testbed for social science research and large language model (LLM) applications in political domains.

Fields of Study & Subjects

Computational and Text Analysis Methods Cultural and political discourse analysis Sociopolitical Dynamics in Russia

Publication details

Journal / source
Harvard Dataverse
Publication date
13 January 2026
Document type
Dataset