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Dygres – The privacy focused social media without ads and algorithms

Hacker News

Dygres – The privacy focused social media without ads and algorithms

Hey Hacker News, excited to reveal the alpha for dygres! The no nonsense, 100% free to use social media aimed at protecting your data and elevating the way we see online communication. Having been a social media user since the myspace days, I had become disillusioned with how far social media has strayed away from communicating and how much it has gravitated towards advertising, pushing agendas, misinformation and silencing critics. My goal with dygres is to build a social media that operates on its own global independent network, where users are in total control of their data, the content they see and are compensated for the content they create among many other yet to be revealed features. Some of the planned features for dygres: Designed with distributed governance in mind so that the userbase plays an active role in the platforms evolution and management. With no algorithms in play, the userbase effectively decides what rises to the top and what fades into obscurity. This makes trending content a natural response to the collectives emotions, likes and dislikes. This also ensures that true creativity and originality is now rewarded rather than obscured in favor of likeness based on an algorithmic evaluation of what's trending or consumed. A tiered verification system ensures any content you see weeds out bad actors and fake accounts. Built in checks that trigger at certain account milestones ensure that the verification isn't a one and done deal. A natural lifecycle for every post to prevent any horse beating. No advertisers means we do not collect or sell your data to any third parties. In fact you can delete your account at any time which erases your existence from the platform. The ad free nature of the platform helps maintain a focus on user generated content freeing you from distractions and a need to be constantly reminded to buy something. To celebrate the launch of this alpha, I have added a small feature that is in a very early stage. Internally its called "yggdrasil". Every user gets a sign up link that they can share and successful sign ups add to a tree. Overtime this feature will develop and sign ups will form a picture of of the online user base. Hopefully it works at scale . My link to sign up to dygres: https://dygres.com/share/drpiratecaptain The journey for dygres is a long one but this alpha has been a long time in the making and rather than seek perfection, I am moving to seek as much feedback as possible at this early stage so that future development is guided by user input rather than the beliefs and opinions of a small group of people. On a final note, I just want to say that I know the platform is very bare bones and lacks a lot of the features that the biggest platforms have at the moment. This however is a completely bootstrapped platform built with the dev support of a very small team so please forgive the very spartan nature of the build. A roadmap exists to evolve the platform further and introduce features that will take the user experience to the next level. Thank you for taking the time to read my post and checking out dygres.

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
93%93% 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: user, new · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, lua · Missing: https docs, just released, open source
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: bootstrapped, 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 · Strong signals: reward, introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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