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Using ChatGPT to track stock mention sentiment (and mapping over price)

Hacker News

Using ChatGPT to track stock mention sentiment (and mapping over price)

Monkeemath is set up to scrape comments across Reddit that include a stock ticker. It then uses ChatGPT to determine whether the comment is bullish or bearish on the outlook of the ticker. This data is then used to create the charts and tables you see across the site. -A page that maps the sentiment of a given stocks mentions mapped over the price movement of the stock. -A page showing you the percentage chance of a stock going up or down based on the sentiment of mentions the previous day. -Theres also a prediction mini game set up, so make a profile and earn your spot on the Monkeemath user leaderboard.

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Actual performance

20points
5comments
Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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: user, chatgpt, using · Missing: mac, agents, macos
67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% 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
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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