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A news feed built to minimize misinfo

Hacker News

A news feed built to minimize misinfo

Hi HN -- I'm one of the cofounders of Forth, a news feed for news. ( https://www.forth.news ) Today seemed like a good day to share widely. My cofounder and I are former journalists, who know how important it is to be able to trust the news that you read. Today, a huge number of people -- especially the under-40 set -- are getting their news from social media, even though it's being overrun with misinformation, disinfo, propaganda, and just made up stuff. We decided that if we were going to doom scroll, we'd want the stuff we're reading to be true. All of the posts on the site come from real journalists. They are who they say they are. I know journalists are not always held in the highest regard on this site, but I will point out -- their livelihoods come from a reputation for accuracy. Sure, humans get things wrong, but a responsible journalist check out a story before posting, and will correct the record if they make a mistake. That's what we expect, and it's listed right in our Editorial Policy. ( https://www.forth.news/docs/editorial ) Please let me know what you think, and if you find this helpful. Jared

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Actual performance

1points
2comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
34%34% 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
21%21% 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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