Teledash

Research and analysis software for Telegram

Teledash is a web application that simplifies research and analysis of the content on Telegram.

Repositories

• Frontend
• Backend

Features

One or more Telegram accounts can be linked to Teledash. The content will be downloaded and processed periodically.

Search

With the help of the web interface, all channels, groups and chats can be searched with various parameters. For example, you can search for messages from a certain period in certain channels or messages from specific users.

Text and speech recognition

Automated text recognition (OCR) is used to recognize and save text on images. In addition, voice messages can automatically be transcribed (ASR) in the background and stored as searchable text. The quality of the results depends strongly on the quality of the audio recording as well as the speech model used. Models for text as well as speech recognition can be manually improved or trained if necessary.

Metrics

Teledash regularly collects statistical data on the activity and growth of channels and groups, enabling quantitative analysis.

Storage

Media such as videos, photos, and voice messages can be automatically downloaded and stored in a MinIO instance or in S3-compatible cloud storage.

Export

All collected data can also be accessed and filtered via a REST API for further processing of the content by third-party software. API endpoints can be tested using Swagger. mongoexport optionally allows the export of complete data sets as CSV or JSON.

Future development

Teledash will be further developed and tested in journalistic and scientific contexts in the future. Feel free to get in touch.

Terminology

• Chats are groups, supergroups and channels. (Private conversations won't be scraped and stored by teledash).
• User are users and bots.
• Messages are messages that contain text or media (attachments)

Citation

Please cite Teledash in your publications if you used it for your research:

@misc{teledash_2022, 
  title={Teledash – analysis and research software for Telegram}, 
  url={https://github.com/democ-de/teledash}, 
  author={Weichbrodt, Gregor and Stanjek, Grischa}, 
  year={2022}
} 

Acknowledgements

• Funded from September 2021 until February 2022 by