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See the economic cost in real-time of social harm in real-time

Hacker News

See the economic cost in real-time of social harm in real-time

I wanted to create clarity between (the many) studies about social media harm and true costs (aka externalities). I built an interactive calculator where you can load any peer-reviewed paper and instantly see its economic impact. Example: Load the Yale 2024 mental health study → calculator shows $280B/year in youth treatment costs alone. Add the Stanford polarization paper → another $500B in lost productivity. Total damage: 2.4% of GDP. The vision: Make externalities of social media (human suffering, suicide, depression, etc.) visible. Try it: https://suffering.social/ Click any study, watch the numbers update in real-time. The methodology is transparent—you can adjust multipliers and see how assumptions change outcomes. Open to suggestions. Trying to make the world 1% safer for children. Also - this may underestimate costs as these are mostly summaries of child-harm studies, many adults not included.

Visit productView on Hacker NewsJun 29, 2025
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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% 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 NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
50%50% 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
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
32%32% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
24%24% 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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