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www.sopajs.org - simple SOPA banner for your website

Hacker News

www.sopajs.org - simple SOPA banner for your website

Y'all, I've been reading about the "nuclear option" that some internet giants are considering in order to highlight SOPA and I wondered why they didn't just put a banner saying to "Pay attention to SOPA" on their sites. I realized that it would only take a bit of time to build the service, so I did. It's built with Python, App Engine (my first time using it), Twitter's Bootstrap and GitHub. Has some rudimentary geolocating included so that politicians can be highlighted. It's a very early version (ie. I only have data for CA politicians), but I figured HN would enjoy seeing it early, especially since it needs more love around: * Increasing the list of SOPA supporters. * Improving styling. * Increasing functionality. Usage: just add the following to your page: <script type="text/javascript" src="//sopajs.appspot.com/sopa.js"> </script> Site: http://www.sopajs.org Code: http://github.com/sopja/sopajs * Bonus points to the first person to point out that the domain is registered on GoDaddy...

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best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps, using, code · Missing: mac, agents, macos
47%47% 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: ide, io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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21%21% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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