Knowledge, Trust, Security and Covertness In Massively Distributed Social Platforms: An Epistemic Networks Approach

TL;DR

This paper introduces an epistemic networks approach to analyze how knowledge, trust, security, and covertness influence user behavior and network dynamics in large-scale social platforms.

Contribution

It presents a novel epistemic networks framework to characterize knowledge states and flows, linking platform structure to social network behavior.

Findings

Epistemic structures significantly impact user interactions.

Knowledge flow patterns influence social network evolution.

The approach offers new insights into platform-user dynamics.

Abstract

Social networks seeded, crystallized and structured by large-scale social platforms like Facebook, LinkedIn, Slack, Twitter, WhatsApp, Instagram and WeChat exhibit complicated epistemic structures and dynamics that arise from the nature of interactive knowledge that users/participants possess, share and shape. What users know about what other users know, about what other users know they know, and so forth, plays an important role in channeling user behavior on the platform as well as the structuring and dynamics of the social network the platform engenders. We use a novel approach to characterize knowledge states and flows in social networks, based on epistemic networks, or epinets, to study the relationship between the structure of platforms and the structure of social networks that form on them.