SR Case: Algoritmernes Magt / The Power of Algorithms

A technical prototype built for an SR Case (Studieretningsprojekt) at HANSENBERG Tekniske Gymnasium, examining the intersection of Programmering B and Kommunikation & IT A.

Overview

This application simulates a social media recommendation algorithm as a "Black Box." It tracks two types of behavioral signals — linger time (how long you look at a post) and active engagement (likes, comments, shares) — to calculate user interest weights (pitsTags). The feed is then dynamically re-ranked to prioritize content matching those weights, offering a hands-on demonstration of how Filter Bubbles and Echo Chambers are technically constructed.

Getting Started

Option A — Download a Release

1. Grab the latest build from Releases
2. Run winx86-64.exe or win-arm64.exe depending on your machine

Option B — Build from Source

1. Clone the repository:

   git clone https://github.com/NoahGNielsen/SR-Case---Algoritmernes-Magt.git

2. Install the .NET 10.0 SDK
3. Open the solution in Visual Studio 2022 or later and build the project

Usage

• Launch the app to start the feed
• The algorithm passively tracks how long you view each post
• Click Like, Comment, or Share to actively signal interest — the feed will re-rank on the next refresh based on those tags
• Click New Post to inject your own content into the system

Project Structure

SR-Case---Algoritmernes-Magt/
├── src/                   # Source code
├── data/                  # Example data
│   └── assets/images/     # Post images
├── docs/                  # Screenshots and documentation assets
└── README.md

License

Distributed under the Apache License 2.0.

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Developer: Noah G. Nielsen
School: HANSENBERG Tekniske Gymnasium