
How It Works
MindMint has a smooth ecosystem of behavioural mining, predictive analytics, and algorithmic nudging.
Step 1: Onboarding
Users join by connecting:
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Social media accounts
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Calendars
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Fitness trackers
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Browsing histories
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Microphone permissions
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Sleep monitoring apps
This allows the platform to develop a complete emotional identity profile within minutes.
Step 2: Behavioural Tracking
The site constantly monitors:
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Typing speed -
Scrolling habits -
Facial expressions -
Voice tone -
Online purchases -
Attention duration
With machine learning systems, MindMint detects instances of distraction, insecurity, motivation or emotional vulnerability.
This we refer to as empathetic optimisation. It is sometimes referred to as surveillance capitalism by the critics.
Step 3: Algorithmic Recommendations
The recommendation engine to the mind mint is based on choice architecture to influence user choices. We make decisions not to give freedom to users but make things easier:
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What is the first content? -
Whom are friends of priority? -
Which products appear to be emotionally needed? -
What are the habits to be rewarded?
These recommendations are perceived as individual empowerment to users and silently the platform increases time on screen and advertising performance.
Step 4: Community Participation
Participatory culture helps the ecosystem to prosper. The users willingly develop productivity tips, inspirational updates, introspective feelings, and self-betterment challenges that bring more users to the platform.
Each upload enhances the algorithm. All interactions enhance network effects. All of the dependencies enhance the scalability of an ecosystem.
Notably, this valuable labour is free of charge as the users are compensated with exposure, social recognition and digital badges.
Step 5: Monetisation
Lastly, access to behavioural data generated by users is sold to advertisers, employers and investors.
MindMint thus attains sustainable development by a lean platform model where users contribute:
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The content -
The labour -
The emotional data -
The social engagement -
Market value of the platform.
In the meantime, the responsibility of mental health outcomes, algorithmic addiction, and emotional exhaustion is kept to a minimum at MindMint.