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How to get around the Wikipedia blackout (if you have to)

Hacker News

How to get around the Wikipedia blackout (if you have to)

I whole heartedly support the protests against SOPA and PIPA, but also recognize that Wikipedia has become an essential service for a lot of people. If you need to get around the black out, and read something on wikipedia, go to the page you need, then put this in your address bar and press enter ... javascript:(function(){$("#mw-sopaOverlay").attr('style', 'display:none'); $("#mw-page-base, #mw-head-base, #content, #mw-head, #mw-panel, #footer").attr('style', 'display:block;');})(); Like I said, this isn't meant to detract from any of the protesting. Just helping out people who are aware, and *actively opposed to these two bills.

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
62%62% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% 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
41%41% 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
24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
16%16% 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.

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