AI tool to guess your personality from your tweets

Hacker News

I was curious how these latest LLMs would perform when personality profiling someone based on their tweets (things like someones core interests, political leanings and even more obscure stuff like personality type). Results were interesting (at least to me) so I put together a dashboard. Initially I was going to allow users to submit their own username through a self-service portal but that's scrapped for now as Twitter management are yet to finalize some API reforms that could kill it. The project is really quite simple. It uses the Twitter API to get prominent recent tweets, feeds these into GPT-3, parses the response (output format is defined strictly in the prompt) and displays these graphically client-side. Anyways hope you enjoy and feel free to ask any questions!

Visit product View on Hacker NewsMar 17, 2023

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Actual performance

4points

1comments

Did not reach leaderboard

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

78%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.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

49%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: user · Missing: mac, agents, macos

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

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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, 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.

Correct prediction on native model

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