Anthropomorphic Visualization of Twitter Style

Hacker News

Wanted to share this project the community. We're 3 brothers who work on a variety of projects on nights and weekends. The latest was inspired by a desire to look at what successful startups are doing with Twitter and in social media. We put this framework together to make comparing twitter accounts as easy as possible. Biggest difficulty was trying to squeeze the most out of the twitter API limitations as possible. We would rolling our own distributed Twitter request API using multiple accounts. We'll see how it holds up. Feedback appreciated! Tech Used: PHP, Processing.js, MySQL, Lil JQuery, Twitter API

Visit product View on Hacker NewsJun 11, 2012

Share card

Actual performance

1points

2comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

86%86% 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, using · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

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

34%34% 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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

17%17% 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.

Correct prediction on native model

Similar products

Twitter stream visualization52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Twitter stream visualization

Hacker News3

Twitter Graph Visualization64%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Twitter Graph Visualization

Hacker News4

Bubbles – A minimalist visualization of what's new on Twitter61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bubbles – A minimalist visualization of what's new on Twitter

Hacker News32

QuakeMap – Earthquake visualization61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

QuakeMap – Earthquake visualization

Hacker News3

Bosnian census visualization61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bosnian census visualization

Hacker News5

Z80 Compiler Visualization66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Z80 Compiler Visualization

Hacker News109

LLVM profiling visualization55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LLVM profiling visualization

Hacker News3

Correspondence - visualization of translations43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Correspondence - visualization of translations

Hacker News1

Hyperlapse Visualization61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hyperlapse Visualization

Hacker News2

De Jong Attractor visualization61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

De Jong Attractor visualization

Hacker News15

Browse all products Analyze your launch