Yo

You can’t rely on motivation to quit social media

Hacker News

You can’t rely on motivation to quit social media

How many times did you tell yourself that you will quit social media apps? I’ve done it multiple times, disabled my Facebook and instagram accounts when I felt motivated to do so, only to enabled them back again whenever my motivation faded and I felt bored. Now, I don’t think that these social apps are completely evil, if you simply control the amount of time you spend surfing them. That is why I designed and built an app that helps me limit the amount of time I spend on these apps and so far it has been effective. The point of the app is simple, to help you reduce your screen time and limit addictive app usage. I really think that negative reinforcement is one of the best ways to build habits, which is why I included it in this app. Do you like watching video ads? I’m thinking you hate them. With this app, you can launch an annoying video ad if you’re about to access one of your blocked apps. If you find yourself regularly and mindlessly launching social apps, this little app will definitely help you overcome this addiction. If you are interested in using the app, it’s available for android users. Disclaimer: Even though this is an app I built and this might look like self promotion I just want to say that this app has helped me and I think that it can help others as well. If you can’t afford the application after the free trial, but you find it to be helpful, I will personally help you out with a free version.

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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: apps, user, using · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, video · Missing: mobile apps, ios, entrepreneurs
66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, 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
35%35% 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
33%33% 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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