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New (yet another) android hacker news app
Hacker NewsNew (yet another) android hacker news app
Hey guys, this is something I've been working on for the past couple of weeks. I made this because I wanted something read HN that was both minimal and followed android guidelines. Website (with screenshots): http://dwak.io/holo_hacker_news/ Source code: https://github.com/dinosaurwithakatana/holo_hacker_news G+ community for becoming a tester: https://plus.google.com/communities/112347719824323216860 Let me know what you guys think, thanks!
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Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting78%78% 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: google, new, code · Missing: mac, agents, macos61%61% 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 released52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews33%33% 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, revenue21%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, crypto0%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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