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Dopamine Blocker – break your Facebook habit

Hacker News

Dopamine Blocker – break your Facebook habit

Hey everybody, I threw this together yesterday as a side project to make my first chrome extension. https://chrome.google.com/webstore/detail/dopamine-blocker/c... Dopamine Blocker is a tool to help break your social media addictions. Every time you visit your favorite social media site, your brain gets a hit of dopamine that keeps you coming back again and again. Dopamine Blocker attempts to breaks that cycle. Now, instead of getting a hit of dopamine when you visit the social media site, you will be faced with an annoying alarm and a rapidly moving page that is hard to read. Your brain won't get the dopamine you crave and you will hopefully stop subconsciously associating social media sites as a dopamine source. Currently works with: Facebook, Hacker News, Reddit, Twitter, and Youtube. Each site can be turned on and off in the options page for this extension. Let me know what you think!

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% 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: google, new · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
38%38% 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
22%22% 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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