What's hot on HN? A visualization of trending topics on HN

Hacker News

I was curious about the most discussed topics on HN over time, so I started analyzing and categorizing all front-page posts with a simple LLM workflow. The result is an interactive chart that displays the trending topics across different time frames. Although the analysis is still relatively basic, I think it provides an interesting perspective on our community. It will be cool to observe changes over a longer time horizon, such as the rise and fall of topics like web3 and AI.

Visit product View on Hacker NewsMar 17, 2024

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, 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: visual · Missing: mac, agents, macos

51%51% 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

41%41% 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 · Missing: plus, platform, intuitive

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting

19%19% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: web3 · Missing: chat, crypto, cryptocurrency

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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