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Jabble – a collaborative fact-checking platform

Hacker News

Jabble – a collaborative fact-checking platform

Hello HN, we are three researchers (Felix, Jonathan, Johannes) and over the past years, we've been doing research on polarization and misinformation. This is our prototype for a platform for collaborative fact-checking. What we have so far: - automated detection for rhetorical fallacies in posts What we are building next: - calculate fact check results taking all the votes and comments in a thread into account - game theoretical reputation system with incentives for honesty - bias correction for votes with matrix factorization (similar to Community Notes) - crowdfunding of fact checks (money distributed to contributors based on the effectiveness of their comments and votes) We are grateful for feedback!

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
46%46% 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
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
26%26% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · 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
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

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