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DeleteX – A webapp to delete your old tweets using a userscript

Hacker News

DeleteX – A webapp to delete your old tweets using a userscript

Hey HN, With Elon Musk's recent restrictions on Twitter's free API, many services for managing old tweets have become unavailable or paid. That's why I've developed DeleteX, an open-source solution old tweets without relying on third-party apps or paid services. How it works: 1. Upload your X (Twitter) archive 2. Filter and select tweets to delete 3. Generate a custom userscript 4. Run the script in your browser console This approach ensures maximum privacy and security, as you maintain full control over your data and the deletion process. The webapp is live at deletex.wastu.net, and the source code is available on GitHub. Feedback is welcome.

Visit productView on Hacker NewsSep 22, 2024
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
84%84% 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 · Strong signals: apps, user, using · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
50%50% 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 · Strong signals: apps, users · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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