To mute words on Twitter in batches, I created a browser extension

Hacker News

Hello HN community :) For a while now I've been watching my Twitter feed fill up with more and more crap. The fact that it's now possible to monetise your tweets has made things even crappier. At the same time, adding words to mute is a pain. First you have to find the option, buried deep in Twitter's settings, and then you have to add them one by one. So I came up with the idea of writing a little browser extension that lets you add lists of muted words, which can come from more or less anywhere, as long as they're in a certain format (a multi-line text file or a JSON array). The extension doesn't collect any data, you don't need an account to use it, and you can store your lists anywhere (although I'd recommend Github gist or Pastebin). To be honest, I made this mainly as an exercise to learn how a browser extension works and how to make one, but if it's useful to people, that's great! Feel free to let me know what you think and give it a try. If there's ever an audience for it, I'm thinking of taking it further by adding lists of people to mute, extracting your existing list of muted words from Twitter, etc.If you have any other ideas for development, I'd love to hear from you.

Visit product View on Hacker NewsAug 23, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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