The best way to discover web comics

Hacker News

I came up with the idea for this site a couple weeks ago and spent a few days hacking together an MVP. The basic premise is that there are two opposing issues surrounding web comics: sharing & copyright infringement. Sites like Pinterest make it easy to share comics, but people share the comics in full with no requirement to link to the original source. Other sites like Reddit are sensitive to copyright, thus only showing text links, but it's a very non-visual way of browsing highly visual content. So I had the idea that showing only the first frame of each comic serves the needs/wants of both creator and audience. The audience gets a fun visual way of browsing all of the latest web comics. But only getting the first frame, they must click through to the original source if they want to enjoy it in full. Thus, the creators receive 100% of the deserved traffic, which comes with their own ad impressions and anything else they are promoting on their websites. To me, that's kind of a win-win. I'd love to hear any thoughts! Link: http://www.justthefirstframe.com

Visit product View on Hacker NewsMar 2, 2012

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

85%85% 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.

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

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, 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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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.

Correct prediction on native model

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