Privacy Focused News, Apps and Services Curated in One Place

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https://privasim.com/ Approximately a year ago, I decided to create a simulator game. A Privacy Simulator where you get users, mine their data and sell those data to other people the main purpose was to educate people on how exactly data mining and data collection is being done by Tech Companies in a very easy and fun way. I posted the dev updates on the YouTube channel (you can still see the Devlogs), the first Devlog was posted on 5th of Nov 2018 (Later I realized that it shares the same theme with the V Movie and Guy Fawkes Holiday). I published the demo version on itch.io back in April of this year and someone donated with a message: "Keep up the good work. I'm a cybersecurity instructor and we are always looking for more tools to teach privacy and security (especially multiplayer games) so it's good to see something like this being made" And I later realized that being just a game was not enough. I did this whole research thing on privacy, blockchain and decentralization. I have invested a few on altcoins a while back in 2018 and most of them did not see the light of the day, I saw the problem. I have curated Privacy focused news, apps and services so you can just go to these sites in one click. Apologies if you are experiencing some technical difficulties, it's still in alpha stage but I am planning to improve it. I have included two call to action buttons at the bottom to support and improve the Privasim. It's still on very early stages so any feedback and support is very much appreciated. Thank you all and hope you'll like it! David

Visit product View on Hacker NewsSep 26, 2019

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best fitHighest predicted score across all platforms for this description.

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nativeThis product was originally launched on this platform.

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37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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