A target list in an evening, not a week
Instead of searching catalogues by hand, you set a topic and get a set of channels and chats you can already work with.
Telegram parsing: how to build a dataset of channels, chats and members
Collect a list of channels, chats or people on your topic in one pass, then send it with one button to the module that will work with it. Below: which parser to use, how not to drown in junk and where to get a ready base if there is no time to collect.
- Channels and chats by topic
- Members and commenters
- Dataset straight to a module
In short
Telegram parsing is collecting channels, chats, their members or messages into a list that modules then work with. TeleTraff has four parsers: Channels, Chats, Members and Messages. Channels and chats are found by keywords, from samples or both at once. What you collect is stored in My datasets, and the Use button sends a dataset to a module with no file export.
TeleTraff editorial teamUpdated: Checked in the panel
Datasets do not get lost between tabs
Everything you collect stays in My datasets. Open a set a month later and it is still there.
A module gets the dataset without copy-paste
Use offers the modules that can work with this type of dataset. Nothing to download and upload again.
Which parser to use for the task
There are four parsers, and each answers its own question. Each one is covered in detail in the parsers guide.
- Channels. You need a list of targets to comment and react under, or competitors to study.
- Chats. You are looking for where your audience talks: such chats suit Neurochat and member collection.
- Members. You need people, not targets: for inviting, mailing or masslooking. The parser collects both chat members and people who comment on channel posts.
- Messages. It pulls contacts out of conversations: phone numbers, @usernames, invite links, e-mails, links and wallets. This dataset can only be exported; it does not go into modules.
Collection modes: search, similar and deep
The channel and chat parsers have a Collection mode. Here is how the modes differ.
| Mode | What it starts from | When to use it |
|---|---|---|
| Search | The keywords you entered | You know how the niche talks and want the obvious targets |
| Similar | Samples: @usernames or t.me links, or a saved dataset | You already have a couple of good channels and need neighbours |
| Deep | Search and similar together | You need wide reach and can wait longer |
How to collect a target list in one pass
A list is easiest to build from narrow to wide.
- 01
Start with the words the niche uses
Not "crypto" but "futures signals" or "altcoin analysis". Narrow words bring less junk.
- 02
Widen the results from the best finds
Take a couple of channels that are definitely yours and run the Similar mode from them.
- 03
Drop places where you cannot write
Comments need channels with open comments. Look through the results and remove dead channels and foreign languages.
- 04
Send the dataset to a module
The saved set opens in My datasets. The Use button opens the Use dataset in a module window with the modules for this type of dataset.
Where a collected dataset goes
The module depends on what you collected. The Use dataset in a module window offers the right ones by itself.
| Dataset type | Where it can be sent |
|---|---|
| Channels | AI commenting, mass reactions, warmup, reporter |
| Chats | AI commenting, mass reactions, warmup, reporter, Neurochat |
| Members | Mailing, inviter, masslooking, reporter |
| Messages | Export only |
How a dataset gets to work
A parser is only as useful as how fast its dataset reaches a module. Here is what that looks like on screen.
Where to get a channel base if there is no time to parse
Open the open base of channels and chats. It holds about 2.8 million channels and chats sorted into sections. Sections, counters and the first 20 sources of each section are visible without sign-up.
After a free sign-up you get the full list with filters by ER, comments and activity, sets for modules and export. Per month you can export 5,000 rows free and on Starter, 25,000 on Pro and 100,000 on Ultimate.
A common way to work: take a section of the base as a starting point and collect what is missing with a parser.
Raw results are not a dataset yet
A search by a broad word brings everything: dead channels, foreign languages, targets without comments. Send such a list straight into AI commenting and the accounts will spend time on empty places. Look through the results, remove the extra and only then press Use.
Terms on this page
Questions and answers
How is Search different from Similar?
Search goes by the keywords you entered. Similar starts from samples: @usernames, t.me links or a saved dataset. Deep does both, so it is wider and slower.
Can I collect members and invite them right away?
Yes. Collect members, open the dataset in My datasets, click Use and choose the inviter. With Continue the dataset using previous run results on, it skips people already invited and known refusals.
What do I do with a Messages dataset?
Export it. It collects contacts from conversations: phone numbers, @usernames, invite links, e-mails, links and wallets. Such a dataset does not go into modules.
Why parse if there is an open base?
The base covers popular niches. A narrow topic, fresh channels or the members of a specific chat still have to be collected with a parser.
How many rows can I export from the open base?
Per month: 5,000 rows free and on Starter, 25,000 on Pro and 100,000 on Ultimate.
Do I need to install anything?
No. The panel runs in a browser on a computer and on a phone.
Read next
Other sections
Collect your first dataset for your niche
Start with the trial: 3 days with no card, every module including parsers. The clock starts with the first account you add.