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The Pushshift Telegram Dataset

Authors: Jason Baumgartner; Savvas Zannettou; Megan Squire; Jeremy Blackburn;

The Pushshift Telegram Dataset

Abstract

Messaging platforms, especially those with a mobile focus, have become increasingly ubiquitous in society. These mobile messaging platforms can have deceivingly large user bases, and in addition to being a way for people to stay in touch, are often used to organize social movements, as well as a place for extremists to congregate.In this paper, we present a dataset from one such mobile messaging platform: Telegram. Our dataset is made up of over 27.8K channels and 317M messages from 2.2M unique users. To the best of our knowledge, our dataset comprises the largest and most complete of its kind. In addition to the raw data, we also provide the source code used to collect it, allowing researchers to run their own data collection instance. We believe the Pushshift Telegram dataset can help researchers from a variety of disciplines interested in studying online social movements, protests, political extremism, and disinformation.

Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Computers and Society, Computers and Society (cs.CY), pushshift, Computer Science - Social and Information Networks, Telegram

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
39
Top 10%
Top 10%
Top 10%
544
328
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