chat-replay-downloader VS word_cloud

you can use this one chat downloader instead of pytchat for getting messages in the chat, they also have found a way to enable to get membership chats which we use in our server

YouTube Chat Downloader: https://github.com/xenova/chat-downloader

Acquisition of raw data : chat-downloader

It is fairly easy to write a script in Python to generate SRT files however, so you could probably integrate it into yt-dlp somehow. See also https://github.com/xenova/chat-downloader/issues/117 for an example of how this may be done, if you're into that sort of thing.

Credit : python with numpy, matplotlib, scipy, jupyter, chat-downloader

There's a solution for downloading chat replays but I can't get it to work and don't know enough about Python to figure it out like I did with youtube-dl. Comment archives are less simple than they seem aside from copy-pasting, since sites like wayback machine can't seem to get over the paywall like the other two solutions can.

by using chat_downloader i was able to run it with the message_types parameter like this:

chat-downloader was used to fetch chat data from the council stream.

Other resources: Youtube chat-downloader Python Wordcloud Library

https://github.com/xenova/chat-downloader Allows downloading of a live chat from YouTube or Twitch.

wordcloud to make the word clouds

- Logo with WordCloud. The texts used were from the plot/synopsis from the Wikipedia pages of the top 20 anime according to MyAnimeList (excluding anime from the same series. I'm looking at you Gintama).

Here's a GitHub issue that tracks this.

Word arrangement generated using the wordcloud Python package with a custom placement mask (skull design by me) and custom color function. Common English words removed before processing.

After reading this tutorial you should now be able to generate your own Wordcloud using Python. Checkout the WordCloud for Python Documentation. Use your imagination and have fun. Please leave like or comment if you found this article interesting!

If you are proficient with Python then there is also the wordcloud library (and its homepage/documentation) to make a custom word cloud for yourself rather than relying on TagCrowd. For example, I noticed that using the HasteBin as a URL source caused TagCrowd to put some gibberish words in the cloud, like “donaeurtmt”, which do not appear when simply pasting the raw text into the text field.

The project is very heavily based on https://github.com/amueller/word_cloud

A quick and easy way to get some context into anything being mentioned ensure the CSV is only the responses and run it through a word cloud generator in Python to determine what those keywords are. That should help you see what your customers are at least mentioning and then go from there to look for surrounding context.