Labeled Datasets for Research on Information Operations
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916488461418496 |
|---|---|
| author | Seckin, Ozgur Can Pote, Manita Nwala, Alexander Yin, Lake Luceri, Luca Flammini, Alessandro Menczer, Filippo |
| author_facet | Seckin, Ozgur Can Pote, Manita Nwala, Alexander Yin, Lake Luceri, Luca Flammini, Alessandro Menczer, Filippo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10609 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Labeled Datasets for Research on Information Operations Seckin, Ozgur Can Pote, Manita Nwala, Alexander Yin, Lake Luceri, Luca Flammini, Alessandro Menczer, Filippo Computers and Society Social and Information Networks 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. |
| title | Labeled Datasets for Research on Information Operations |
| topic | Computers and Society Social and Information Networks |
| url | https://arxiv.org/abs/2411.10609 |