I accidentally started a movement – Policing the Police

Hacker News

About a week ago, a blog post I wrote about my experience scraping and analyzing public court records data to find dirty cops got very popular on Reddit and HackerNews. https://lawsuit.org/keeping-cops-accountable/ As a result, I started a slack channel for others who were interested in scraping public court records, in an effort to create the first public repository of full county level court records for as many counties as possible. Now, less than a week later, 71 journalists, data scientists, developers, and activists have joined. We are now organizing this grassroots project, and I couldn't be more proud or excited.

Visit product View on Hacker NewsMay 26, 2020

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

69%69% 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 HuntOn track for Day 1 leaderboard · Strong signals: slack, new · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

24%24% 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

16%16% 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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