Chat Analytics

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A web app that takes chat exports from supported platforms and generates a single HTML file containing information, statistics and interactive graphs about them. Privacy is its main concern; chat data never leaves the device when generating reports. Selfhost with Docker!

💬 MESSAGES	🅰️ LANGUAGE	😃 EMOJI	🔗 LINKS	📞 CALLS	🌀 INTERACTION	💙 SENTIMENT	📅 TIMELINE

You can interact with the demo here!

Chat platform support

You can generate reports from the following platforms:

Platform	Formats supported	Text content	Edits & Replies	Attachment Types	Reactions	Profile picture	Mentions	Calls
Discord	json from DiscordChatExporter	✅	✅	✅	✅	✅ (until link expires)	✅ (as text)	✅
Messenger	json from Facebook DYI export	✅	❌	✅	❌	❌	✅ (as text)	❌
Telegram	json from Telegram Desktop	✅	✅	✅	❌ (not provided)	❌	✅ (as text)	✅
WhatsApp	txt or zip exported from a phone	✅	❌ (not provided)	✅* (if exported from iOS) 🟦 (generic if exported from Android)	❌ (not provided)	❌	✅ (as text)	❌

* not all languages are supported, check WhatsApp.ts.

You can't combine exports from different platforms.
The contribution of new platform parsers is always welcomed 🙂

Privacy & Analytics

Since all chat data always stays in the browser, there is zero risk of someone reading your chats. Note that the report HTML file contains sensitive information (one may reconstruct message contents for every message), so share your reports with people you trust.

The site does not use cookies either and uses a self-hosted version of Plausible. All events do not contain PII and the information is segmented (e.g. 1MB-10MB, etc.). Since I want full transparency, you can check the site analytics here.

CLI

You can generate reports from the command line using npx chat-analytics:

Usage: chat-analytics -p <platform> -i <input files>

Options:
      --help      Show help                                            [boolean]
      --version   Show version number                                  [boolean]
  -p, --platform  The platform to generate for
   [string] [required] [choices: "discord", "messenger", "telegram", "whatsapp"]
  -i, --inputs    The input file(s) to use (glob)             [array] [required]
  -o, --output    The output HTML filename     [string] [default: "report.html"]
      --demo      Mark the report as a demo           [boolean] [default: false]

For example:

npx chat-analytics -p discord -i "exported/*.json" -o report.html

Docker Compose

You can self-host the app using the official docker image provided at https://hub.docker.com/r/mlomb/chat-analytics. Check out the Dockerfile.

Example docker-compose.yaml:

services:
  chat-analytics:
    image: mlomb/chat-analytics:latest
    ports:
      - 1234:80
    restart: unless-stopped

You can map the web interface port as required by changing the port mapping, internal port must be kept to 80.

Docs & Development

You can read docs/README.md for technical details, and docs/DEV.md for development instructions.
In docs/TODO.md you can find ideas and pending stuff to be implemented.

Acknowledgements

• FastText, a library by Facebook for efficient sentence classification. MIT licensed.
• lid.176.ftz model, provided by FastText developers for language identification. Distributed under CC BY-SA 3.0.
• multilang-sentiment, for the translated AFINN database. MIT licensed.
• Emoji sentiment data from the work of Kralj Novak, Petra; Smailović, Jasmina; Sluban, Borut and Mozetič, Igor, 2015, Emoji Sentiment Ranking 1.0, Slovenian language resource repository CLARIN.SI, http://hdl.handle.net/11356/1048. Licensed with CC BY-SA 4.0.
• stopwords-iso for a collection of stopwords in a variety of languages. MIT licensed.
• All the libraries and tools that made this project possible 😀

License

AGPLv3. See LICENSE.