Low moderated social networking sites (SNS) ``have become an important piece of the modern information ecosystem'' (Zannetou
et. al., 2017, p. 405), especially since the stricter content moderation policies introduced by mainstream SNS exacerbated
the growth of low moderated SNS that welcomed deplatformed digital exiles with open arms.
Despite recent indications of an interdependent relationship between the escalation of (far-right) extremism and the uptick of alternative SNS such as Telegram, empirical research on the content of such platforms remains limited.
Online extremism scholars lack open access data collection instruments that facilitate the investigation of how recent political upheavals are echoed on the darker corners of the web.
We approached this research gap by building a scraper that enables the collection of the complete message history of public Telegram chats and channels.
Our data collection instrument as well as an anonymized data set of over 2 million time-stamped text messages, and 217,428 unique URL-s shared by 55,331 users across 174 Dutch-language, public chats and channels will be made public alongside preliminary findings that aimed to examine information flows within the greater public Telegram sphere, and to explore how do these communities link to other sources outside of Telegram.
In a nutshell, we found that the Dutch public Telegram space comprises a highly centralized, albeit weak, community where topically and ideologically different chats and channels seem to cluster together over time.
From news, through far-right extremism, to conspiracy theorizing, Telegram chats and channels were intertwined via overlapping users and overlapping URL-s that mainly linked to mainstream SNS such as YouTube.
Taken together, while our data collection instrument facilitates the investigation of the public Telegram space in a systematic manner, our data set serves as a great resource for scholars who wish to study extremist narratives online by training classifiers on platform-specific corpora.
Despite recent indications of an interdependent relationship between the escalation of (far-right) extremism and the uptick of alternative SNS such as Telegram, empirical research on the content of such platforms remains limited.
Online extremism scholars lack open access data collection instruments that facilitate the investigation of how recent political upheavals are echoed on the darker corners of the web.
We approached this research gap by building a scraper that enables the collection of the complete message history of public Telegram chats and channels.
Our data collection instrument as well as an anonymized data set of over 2 million time-stamped text messages, and 217,428 unique URL-s shared by 55,331 users across 174 Dutch-language, public chats and channels will be made public alongside preliminary findings that aimed to examine information flows within the greater public Telegram sphere, and to explore how do these communities link to other sources outside of Telegram.
In a nutshell, we found that the Dutch public Telegram space comprises a highly centralized, albeit weak, community where topically and ideologically different chats and channels seem to cluster together over time.
From news, through far-right extremism, to conspiracy theorizing, Telegram chats and channels were intertwined via overlapping users and overlapping URL-s that mainly linked to mainstream SNS such as YouTube.
Taken together, while our data collection instrument facilitates the investigation of the public Telegram space in a systematic manner, our data set serves as a great resource for scholars who wish to study extremist narratives online by training classifiers on platform-specific corpora.
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