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Tracking voter discussion of the Presidential debates

Hacker News

Tracking voter discussion of the Presidential debates

Votizen is working to remove the influence of money in politics by making political decision-making more peer-to-peer. We're using Twitter and our API to pull tweets from only registered voters, and showing how the discussion breaks down among the parties. This has never been done before as far as I know, not even by the major media outlets. Please check it out and let me know what you think. If people are interested, we'll work to improve it for the further debates and campaigns.

Visit product View on Hacker NewsOct 4, 2012

Actual performance

44points

29comments

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Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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.

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

30%30% 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

19%19% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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