Published August 25, 2025 | Version v1
Dataset Open

Russian and Ukrainian War-related Telegram Channels

  • 1. ROR icon University of Helsinki

Description

Russian and Ukrainian War-related Telegram Channels Dataset

This dataset provides a large-scale collection of Telegram channels and posts related to the ongoing Russo-Ukrainian war. It captures a wide range of war-related content, including news, commentary, propaganda, and public discussions, making it a valuable resource for researchers studying online information flows, disinformation, and digital discourse surrounding the conflict.

Dataset Structure

1. channels.csv

A CSV file containing metadata for 66,260 Telegram channels.

Columns:

  • id: Unique identifier of the Telegram channel.

  • title: Name of the Telegram channel.

  • date: Channel creation date.

  • fake: Binary indicator (true/false) showing whether the channel is flagged as fake.

  • username: Channel’s username (if available).

  • about: Channel description.

  • pts: Telegram API persistent identifier for the latest event in the update sequence.

  • participants_count: Number of subscribers at the time of data collection.

  • pinned_msg_id: ID of the pinned message (if any).

  • linked_chat_id: ID of the linked chat (if any).

2. leiden_clusters.csv

A CSV file containing clustering results of 3,074 channels, grouped into 8 clusters based on content and interaction patterns using the Leiden algorithm.

Columns (in addition to standard channel metadata):

  • peer_id: Unique channel identifier.

  • cluster: Assigned cluster number.

  • war: Mentions of “war” in posts.

  • svo: Mentions of “СВО” (Special Military Operation).

  • na_ukraine: Mentions of the phrase “на Украине” (in Ukraine).

  • v_ukraine: Mentions of the phrase “в Украине” (in Ukraine).

  • oppo: Mentions of opposition-related terms (definition pending).

  • slava: Mentions of “слава” (glory).

  • sila: Mentions of “сила” (strength).

  • posts_count: Total number of posts per channel.

  • posts_count_wartime: Number of posts published during wartime.

  • last_post: Timestamp of the latest post.

  • ua_symbol: Mentions of Ukrainian symbols.

  • ru_symbol: Mentions of Russian symbols.

  • uk: Share of Ukrainian-language usage.

  • ru: Share of Russian-language usage.

  • antirus: Mentions expressing anti-Russian sentiment.

  • antiukr: Mentions expressing anti-Ukrainian sentiment.

  • war_engagement: Engagement score with war-related content.

  • toxic: Toxicity score of channel content.

  • score: Ideological leaning score (Pro-Russian vs Pro-Ukrainian).

  • side: Channel alignment (Pro-Russian, Pro-Ukrainian, Neutral).

3. post_texts_part_{n}.csv

Multiple CSV files containing post texts, split for scalability.

  • 79,572,856 posts from 4,687 channels.

  • Coverage: 2015-09-22 (earliest channel creation date) to 2024-03-26 (most channels up to 2024-02-01).

Columns:

  • id: Unique identifier of the post.

  • peer_id: Channel ID.

  • date: Post timestamp.

  • message: Post text.

  • views: Number of views.

  • forwards: Number of forwards.

  • edit_date: Timestamp of last edit (if applicable).

4. post_fwd.csv

A CSV file documenting 18,190,690 forwarded posts.

Columns:

  • id: Unique identifier of the forwarded post.

  • peer_id: ID of the channel that forwarded the post.

  • fwd_from_channel_id: ID of the original source channel.

  • fwd_from_channel_post: ID of the original post.

Files

leiden_clusters.csv

Files (49.0 GB)

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Additional details

Related works

Is supplement to
Preprint: 10.31235/osf.io/34qwd_v1 (DOI)

Dates

Collected
2024-03-26

Software

Programming language
Python , R , SQL