dejavu VS TWINT

This doesn't seem hard, you can use something like this to dwoanload the songs: https://stackoverflow.com/a/27481870/6151784 and something like this to calculate how much they match: https://github.com/worldveil/dejavu The question is would you create a (dedicated) server to do your work? Or your own pc? You could also create a very simple page where someone would paste you a YouTube profile URL and you would check all songs of this URL. Also to have a db and save information about the matching and which youtube profiles have alsready been checked. Something like that could work.

If you read the installation.md file it clearly states that it has only been tested on UNIX systems, so you might be on your own trying to get it to wor in windows.

Using neural networks seems complicated, did you tried audio fingerprinting? I have been using this audio fingerprinting library to power this anime song synchronization script. You can check Panako and dejavu too.

I want to say these few seconds match these few seconds from a different audio track. Using dejavu raw has overhead I do not need/want and hence I've been fiddling around with the fingerprint script. When modifying the global variables I can get better hits or worse hits, I will admit that even after reading there recommended article and many other sources, I can't find some good explanations about the mathematics behind the filtering after the specgram has been applied. As far as a I am aware we first apply filters to find/make fine points across the spectrogram after that we only check the distance between points along the time axis not the frequency or a hypotenuse (weird).

I used a repo called https://github.com/worldveil/dejavu to compare audio hashed fingerprints and distinguish the difference between them.

twint is a project that can scrape twitter data via the webpages rather than the twitter API, which means that it can get more than the last 3200 tweets of an account. Unfortunately it seems that the repo was archived and is no longer in development, so I'm not sure if it even still works. It's also a bit heavy on dependencies and is written in Python, neither of which make it easier to install and use.

The tool doesn't work anymore since Twitter changed its APIs, but a good example is twint. Most people in OSINT are not highly technical and don't know their way around a CLI. On the other hand, a CLI tool is one of the quickest, lowest (dev) cost ways to release a tool to the public, and many developers who build tools for the OSINT community do so for free (open source).

You can try twint which is extensive and should be able to do that. Another is via this twitter downloader but might require multiple runs depending on what you want to archive.

They do have examples that don't specify a username such as number 3 on this page or this one on the main page: "twint -g="48.880048,2.385939,1km" -o file.csv --csv - Scrape Tweets from a radius of 1km around a place in Paris and export them to a csv file."

This will motivate researchers to web scrape to circumvent these restrictions. Twint can scrape tweets and it supports proxies. It can also be multi threaded. A huge hassle and it's prone to breaking when the site changes.

The comment I saw said they used this: https://github.com/twintproject/twint