Labeled Datasets for Research on Information Operations

Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs). Some social media platforms have released datasets related to such IOs originating from different countries. However, we lack comprehensive control data that can enable the development of IO detection methods. To bridge this gap, we present new labeled datasets about 26 campaigns, which contain both IO posts verified by a social media platform and over 13M posts by 303k accounts that discussed similar topics in the same time frames (control data). The datasets will facilitate the study of narratives, network interactions, and engagement strategies employed by coordinated accounts across various campaigns and countries. By comparing these coordinated accounts against organic ones, researchers can develop and benchmark IO detection algorithms.

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Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35958
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57

Funders

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article

Labeled Datasets for Research on Information Operations

Alessandro Flammini, Manita Pote, Filippo Menczer, Lake Yin et al.
2 citations
Proceedings of the International AAAI Conference on Web and Social Media
Big Data and Business Intelligence
4.57
article

Labeled Datasets for Research on Information Operations

Alessandro Flammini, Manita Pote, Filippo Menczer, Lake Yin, Ozgur Can Seckin, Alexander C. Nwala, Luca Luceri
article en
2 citations

Abstract

Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs). Some social media platforms have released datasets related to such IOs originating from different countries. However, we lack comprehensive control data that can enable the development of IO detection methods. To bridge this gap, we present new labeled datasets about 26 campaigns, which contain both IO posts verified by a social media platform and over 13M posts by 303k accounts that discussed similar topics in the same time frames (control data). The datasets will facilitate the study of narratives, network interactions, and engagement strategies employed by coordinated accounts across various campaigns and countries. By comparing these coordinated accounts against organic ones, researchers can develop and benchmark IO detection algorithms.

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
University of Southern California (US), William & Mary (US), Williams (United States) (US), Indiana University Bloomington (US)
John S. and James L. Knight Foundation, Craig Newmark Philanthropies, Volkswagen Foundation
Openalex Percentile: Top 6%
Big Data and Business Intelligence
4.57
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Labeled Datasets for Research on Information Operations — Alessandro Flammini, Manita Pote, et al. · Proceedings of the International AAAI Conference on Web and Social Media (2025) | TGRS Research Map | TGRS