Bookmarklet to filter HN by regex-enabled keywords.

Hacker News

This is a small bookmarklet that adds a background color to articles matching keywords, making it easier to distinguish links important to you. Tested in Chrome 27, Firefox 21 and Safari 6.0.5. Preview: http://i.imgur.com/6A3CU6T.png 1. Modify the OPTIONS.color and OPTIONS.keywords properties to your liking. You may use regex in the keywords. Keywords are case-insensitive. 2. Paste the bookmarklet below as the URL to a bookmark. You have to click this bookmark on every refresh, therefore you may want to place it on your "Bookmarks Bar" for quick access. javascript:(function(){var OPTIONS={keywords:["surveillance","nsa","prism","privacy","government"],color:"#f4c3c3"};NodeList.prototype.forEach=Array.prototype.forEach;document.querySelectorAll('.title>a').forEach(function(e){if(e.firstChild.nodeValue=='More')return;if(new RegExp(OPTIONS.keywords.join('|'), 'i').test(e.firstChild.nodeValue)){e.parentNode.parentNode.style.backgroundColor=OPTIONS.color;e.parentNode.parentNode.nextSibling.style.backgroundColor=OPTIONS.color}})})()

Visit product View on Hacker NewsJun 9, 2013

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

52%52% 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.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

26%26% predicted probability of success on TrustMRR, 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

23%23% 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 · Strong signals: arr · Missing: mrr, revenue, profit

11%11% 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.

Correct prediction on native model

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