Lo
Local Emotion Sharing
Hacker NewsLocal Emotion Sharing
Wold be happy for your feedback for a just published site. Currently only focused on one goal. - Simple sharing of your emotion and - Know the mood near your location - Average on simple math - your area is 1 degree wide on rounded values of latitude / longitude. No civic boundaries. - your co-ords get rounded - Currently map is detailed for India only. Will see a better provider later - Users registration is safe with Keycloak. You are invited !
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
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AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting34%34% predicted probability of success on Indie Hackers, 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 released33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% 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, crypto2%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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