MDPI Social Hypernetwork Archetype Classification

Overview

Classify users into one of eight behavioral archetypes by scoring them on three normalized axes -- Score (visibility/influence), Sentiment (affective valence), and Toxicity (harmful language probability) -- then assigning a three-letter label (High/Low on each axis) that describes their engagement pattern. The core principle: archetypes are behavioral patterns observable in data, not personality types or stable traits -- they describe what a user does in a given period, not who they are.

This methodology is based on Ferrara et al. (2025), "Characterizing User Archetypes and Discussions on Social Hypernetworks" (MDPI Big Data and Cognitive Computing, 9(9), 236), which introduced the three-axis archetype framework for characterizing nodes in social hypernetworks.

When to Use

• User-generated content corpus with at least post/comment text and some form of engagement score
• Need to segment users by behavioral pattern rather than a single metric
• Want to understand the interplay between visibility, sentiment, and toxicity in a community
• Analyzing community health, moderation needs, or engagement dynamics
• Preparing user profiles for downstream style analysis where emotional valence constraints matter

When NOT to use: