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Node.js Client for Twitter

Hacker News

Node.js Client for Twitter

Hey everybody, I'd like to share a little project I'm working on, it is a web app that allows you to pull public twitter timeline of any handle. Its still very early stage and I am unsure what features I would like to prioritize so I'm sharing it here for some Feedback :] LINK: https://feederb0t.herokuapp.com Also, if you don't trust the web find our public Github repository here and clone it locally: https://graybot666.github.io/Feederbot-Public/ Looking forward to your feedback, Thanks. P.S. All credit for this work should go to BoyCook [on Github], this project just builds on his and others work.

Visit product View on Hacker NewsAug 14, 2019

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

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

best fitHighest predicted score across all platforms for this description.

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

57%57% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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

13%13% 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, crypto

1%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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