{
  "id": 11054444,
  "title": "What I learned trying to index public Telegram communities",
  "url": "https://urgent.news/2026/09/30/what-i-learned-trying-to-index-public-telegram-communities",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-30T23:17:33.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/viewtglab/what-i-learned-trying-to-index-public-telegram-communities-k4h"
  },
  "original_language": "en",
  "account": "Indexing public Telegram communities is a complex task with many challenges that most people might not anticipate. The metadata exposed by Telegram's public API is sparse, providing only basic information such as a title, description, invite link, and approximate member count. There is no reliable topic or category system, nor language tags, making it difficult to organize content by subject matter. To create a functional catalogue, one must infer subjects from descriptions, titles, and community activity, all of which are inherently unreliable.\n\nOne crucial design decision is distinguishing between channels, groups, and bots. Channels are one-way broadcasts, groups are user-driven conversational spaces, and bots are tools rather than places. Treating them as a single list would make the catalogue less useful, as users searching for discussion groups would be presented with irrelevant broadcast feeds.\n\nLanguage is another significant hurdle. A large portion of Telegram's ecosystem is non-English, and an index that ignores language will likely surface communities that are inaccessible to users. Adding language filtering is a relatively simple enhancement that significantly improves the usability of the index.\n\nOver time, communities can become inactive, rename, or go private, rendering a static index quickly outdated. The most important aspect of maintaining an index is a regular re-verification loop that checks entries periodically to ensure their relevance and accuracy. This aspect, while not glamorous, is arguably the most critical component of a reliable index.\n\nA functional index typically includes several key features: a well-defined topic taxonomy with editorial input, tag and language filtering options, separation of different entity types (channels, groups, bots), a description of each entry, and a snapshot of its activity level. VIEW is one example that incorporates these elements, providing a categorised catalogue of public Telegram channels, groups, and bots with filters for category, tags, and language, along with a member count snapshot for each entry.\n\nWhen evaluating such an index, there are two important caveats to consider. First, the catalogue is extensive and includes a broad range of content, including adult material, which may not be suitable for all audiences. Second, no index of this nature can be exhaustive, so users should treat it as a starting point rather than a definitive list. Ultimately, any index of user-generated communities should be seen as a foundation or starting point for further exploration, rather than a complete solution.",
  "summary": "Telegram has an enormous number of public communities and almost no structured way to discover them. I spent a while looking at what it actually takes to build an index of them, and most of the difficulty is not where you would expect. The metadata problem Telegram's public API exposes very little structured metadata about a public channel or group. You generally get a title, a description, an…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}