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I built Swinton Report for unbiased, user driven news a HN clone.

Hacker News

I built Swinton Report for unbiased, user driven news a HN clone.

I built SwintonReport.com as a clone to Hacker News. I built it mainly for the need for unbiased news for the US and world. I am sick and tired of the biased news show casing things, but not others. It doesn't depend what side your on, but rather what type of news you want to read now. Do you want to read Left Wing or Right Wing. I got tired of reading either or and this was created because of it. While my new favorite place to read news is now the Guardian, I believe there is more than just one solid source for honest real unopinionated news. This is the start of that. Its built on top of ASP.NET and C#, the same framework that powers StackOverflow.com. Its what I knew best to get up and running. I named it SwintonReport.com after John Swinton and what he published in the New York Times. http://swintonreport.com/about

Visit product View on Hacker NewsApr 15, 2014

Actual performance

1points

1comments

Did not reach leaderboard

Launch Intel predictions

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

80%80% 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: hacker news, ide, io · Missing: https docs, excited, just released

56%56% 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: user, new · Missing: mac, agents, macos

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% 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

41%41% 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

14%14% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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