Top Links from Hacker News, Reddit, Techmeme, PH on a Single Page

Hacker News

Hi HN, this is something I created for my personal use and I have been using it daily for a long time now. It’s a page that shows top 25 links from the sources mentioned in the title. Updates every 10 minutes through a cron job and new links are always added to the top. Some more details: It’s using simple heuristics like minimum upvotes/comments to select the links. For techmeme, only the first headline on techmeme.com is considered a top link. For reddit, currently fetching content from only a select few subreddits. It’s just a simple page. No ad. No tracking. It’s the first tab I open in the morning. Suggestions and feedback are welcome. :)

Visit product View on Hacker NewsMay 30, 2022

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Actual performance

131points

64comments

Made the leaderboard

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

70%70% 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, single, using · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, 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.

TrustMRRFits verified-revenue profile · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

50%50% 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

43%43% 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

16%16% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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