Enabling Public Discourse Research with Telegram Data – No Coding Required

By Philip Mai

We are thrilled to announce the release of the new Telegram data collector in Communalytic, our newest computational social science research tool. The new data collector will provide academic researchers with a systematic way to access and study public discourse on one of the fastest growing social media apps.

If you are not familiar with Telegram, it is an encrypted app similar to Meta’s WhatsApp and Facebook Messenger. Launched in 2013 by entrepreneurs Nikolai and Pavel Durov (also founders of Russian social media platform VK), Telegram is now one of the top-5 downloaded apps worldwide with over 700 million monthly active users.

But Telegram is more than a messenger app. It also hosts numerous groups and channels that allow for one-to-many and many-to-many types of communication. These public groups and channels attract millions of users from all walks of life, including governments, politicians, pundits, news organizations, activists and many others. For example, when Russia invaded Ukraine earlier this year, Telegram “became the go-to app for Ukrainians” and while at the same time it also emerged as one of the “main vectors for invasion disinformation”. Telegram’s ease of mixing the public and private, and its lack of a formal mechanism to report illegal content have attracted terrorists and fines from governments over the years. 

Because of this presence of diverse communities and controversial issues, Telegram is beginning to attract the interest of researchers who are keen on conducting independent research in the public interest in areas such as mis/dis-information, hate speech, online extremism to name just a few. However, up until now, only researchers with programming skills have been able to access publicly available data from Telegram. With the introduction of the new Telegram collector feature in Communalytic, we hope to address this access gap by providing an easy-to-use, web-based interface for data collection and analysis of Telegram data.

If you are interested in learning more, here are a few helpful links to get you started with Telegram research via Communalytic:


About Communalytic

Communalytic is a no-code computational social science research tool for studying online communities and discourse. It can collect, analyze, and visualize publicly available data from various social media platforms including Reddit, Telegram, YouTube, Facebook/Instagram (via CrowdTangle) and Twitter, or from a user-uploaded CSV or JSON file.

Communalytic contains a suite of advanced data analytics modules including: a Toxicity Analyzer, a Sentiment Analyzer, a Topic Analyzer and a built-in Network Analyzer. These modules can be used to automatically:

  • detect anti-social interactions (i.e., harassment, hate speech, extremist content, etc.),
  • assess sentiments in online discourse,
  • identify and group together social media posts that are semantically similar and identify latent topics within your dataset,
  • generate and visualize various types of networks, including communication and link-sharing networks, which in turn can be used to identify influencers, map shared interests among online actors, study the spread of mis/dis-information and detect signs of possible coordination among seemingly disparate actors.

For more details, see Communalytic’s Tutorials page.