HN Live – Hacker News in Real Time

Hacker News

I am re posting this because when I had made this post the first time there were a few problem with the site that I had to fix and had not anticipated. I got some nice feedback though, so I thought I'd just make one more post because most of the problems have been fixed. HN Live is an alternative interface to Hacker News which provides all of the data on Hacker News in real time. This allows for the real time viewing of what goes into and leaves the trending page as well as the `newest` section. It is just a personal project, and I would like some feedback if you have any. Thanks Site: http://hnlive.cf Original Post: https://news.ycombinator.com/item?id=10771675

Visit product View on Hacker NewsDec 22, 2015

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Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

46%46% 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

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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