Social Media Platform (Python)

What This Is

A social platform built from the ground up in Python but designed as a research substrate for studying how argument topology shapes opinion dynamics. The structured debate threads aren't a product feature; they're a data collection mechanism. What happens to consensus when you force arguments into a tree structure vs. a flat feed?

This is a live question in computational social science. Reddit, Twitter/X, and Facebook have different thread structures and have demonstrably different polarisation dynamics. Causality is hard to establish because the platform, user base, and content all differ. A controlled platform built for research can isolate the variable.

The Architecture

Client-server design with a clean protocol: all UI is stateless, all state lives in the backend. This makes it easy to run multiple frontend variants against the same backend useful for A/B testing interface changes.

Structured debate threads: unlike flat comment sections, debates are organised as argument trees: claim → response → rebuttal → counter-rebuttal. Each node is typed (claim, evidence, rebuttal, concession). The structure enforces coherent argumentation and makes the debate programmatically analysable.

Database schema designed for analysis: every interaction, view, and engagement is logged with full provenance. The schema is normalised for OLAP queries we want to ask questions like "do users who read rebuttals before the original claim update their views more than those who don't?"

What Makes It Interesting

The platform is simultaneously a product and a dataset generator. Running experiments on real social platforms is impossible without corporate access. A self-hosted research platform lets you:

• Control the feed algorithm and measure its effect on polarisation
• Test whether structured debate threads reduce misinformation spread
• Study influence network formation from day zero

What's Next

• LLM integration: flag logical fallacies in debate nodes in real time
• Quantitative study design: pre-register hypotheses and run controlled experiments
• Federated protocol: connect multiple instances to study cross-community dynamics