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I Built a Twitterbot to Recommend SXSW Parties (Node + Twit)
Hacker NewsI Built a Twitterbot to Recommend SXSW Parties (Node + Twit)
Hi all, I've submitted a post on Airpair about how to build a twitterbot that uses Node and the streaming and RESTful twitter APIs to recommend SXSW parties. I'd love any reviews or constructive criticism. https://www.airpair.com/posts/review/54fcfe16c1534a0c00e6c839 If you'd just like to check out the bot, you can find him at @SouthBotFunWest Thanks HN!
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AppSumoStrong fit for a featured deal · Strong signals: reviews · Missing: plus, platform, intuitive53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released49%49% 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: apis · Missing: mac, agents, macos42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal34%34% 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, revenue17%17% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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