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One Minute News: Your Minimalist Anti-Clickbait News Platform

Hacker News

One Minute News: Your Minimalist Anti-Clickbait News Platform

This is a minimalist news digest site that helps readers understand the biggest news happening around the world in one minute. We work on this as a side project. So why are we doing this? Welp, I myself am a clickbait hater. Sometimes I click into a news story on Facebook just to find out the content is nothing as the title suggests. Born from pure hatred, we have created One Minute News to make sure every headline literally says what the content is about. This helps readers save tons of time filtering out unimportant news just by scanning through the honest headlines. So far, here are the current features One Minute News is offering: - Rewrite clickbait headlines into honest, straightforward, and literal titles. - Filter out unimportant news. - Rank news importance with a rubric-based, time-decayed scoring system - Allow readers to filter news with preferred tags. - Compile periodic digests/briefings that summarize high-scoring articles every 6 hours. - Display the source link back to the original article. - Bookmark news. - Saved preferred tags. Please let me know if there are any future features you want to see. For now, we only have the website version and 0 experience in journalism. If you want to be a part of this anti-clickbait adventure too, let me know.

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
74%74% 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: new · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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.

Correct prediction on native model

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