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A news feed exclusively populated by journalists

Hacker News

A news feed exclusively populated by journalists

Hi HN -- Given all the talk with new the platforms launching recently, I want to share a project. It's called Forth (no relation to the programming language), and it's a news feed for news. Anyone can make an account and curate their own feed through follows, but it's populated exclusively by journalists. Most Americans get at least some of their news from social media, even though they don't trust it. We want to take the good (formatting, brevity, ability to follow who you want), and mix it with real fact-based reporting. Our reporting partners cover all sorts of topics, from local news around the US, to space, chemistry, politics, everything. We're still ramping up, but already have journalists ranging from names you might see on Good Morning America to local radio and newspapers, and all sorts of verticals. It's not social media. It's almost anti-social. No spam, no misinformation, no hate speech. Just headlines. I'd love to hear your thoughts. https://www.forth.news/ Jared

Visit productView on Hacker NewsJul 6, 2023
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
57%57% 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, exclusive · Missing: plus, intuitive, reviews
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% 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
20%20% 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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