Who Contributes to the Knowledge Sharing Economy?

TL;DR

This paper introduces a non-linear model of perishable public goods in social media, revealing that content shelf time critically influences audience participation and causes a fundamental dichotomy in information diffusion complexity.

Contribution

It bridges public goods theory with social media diffusion analysis, introducing a model that highlights content shelf time as key to understanding user participation and content specialization.

Findings

Short-lived content has predictable diffusion patterns.

Long-lived content leads to complex user specialization.

Shelf time is a critical factor in content diffusion dynamics.

Abstract

Information sharing dynamics of social networks rely on a small set of influencers to effectively reach a large audience. Our recent results and observations demonstrate that the shape and identity of this elite, especially those contributing \emph{original} content, is difficult to predict. Information acquisition is often cited as an example of a public good. However, this emerging and powerful theory has yet to provably offer qualitative insights on how specialization of users into active and passive participants occurs. This paper bridges, for the first time, the theory of public goods and the analysis of diffusion in social media. We introduce a non-linear model of \emph{perishable} public goods, leveraging new observations about sharing of media sources. The primary contribution of this work is to show that \emph{shelf time}, which characterizes the rate at which content get renewed, is a critical factor in audience participation. Our model proves a fundamental \emph{dichotomy} in information diffusion: While short-lived content has simple and predictable diffusion, long-lived content has complex specialization. This occurs even when all information seekers are \emph{ex ante} identical and could be a contributing factor to the difficulty of predicting social network participation and evolution.