A picture is worth a thousand words: an empirical study on the influence of content visibility on diffusion processes within a virtual world

TL;DR

This study investigates how content visibility and social network factors influence information diffusion in virtual worlds, revealing that prior visibility is the strongest predictor of content adoption and spread.

Contribution

The paper provides an empirical analysis of content diffusion in virtual environments, highlighting the critical role of content visibility and multilayer social network interactions.

Findings

Prior content visibility strongly predicts diffusion.

Content quality and social activity layers significantly influence adoption.

Diffusion mechanics and neighbor adoption impact content spread.

Abstract

Studying information diffusion and the spread of goods in the real world and in many digital services can be extremely difficult since information about the information flows is challenging to accurately track. How information spreads has commonly been analysed from the perspective of homophily, social influence, and initial seed selection. However, in virtual worlds and virtual economies, the movements of information and goods can be precisely tracked. Therefore, these environments create laboratories for the accurate study of information diffusion characteristics that have been difficult to study in prior research. In this paper, we study how content visibility as well as sender and receiver characteristics, the relationship between them, and the types of multilayer social network layers affect content absorption and diffusion in virtual world. The results show that prior visibility of distributed content is the strongest predictor of content adoption and its further spread across networks. Among other analysed factors, the mechanics of diffusion, content quality, and content adoption by users neighbours on the social activity layer had very strong influences on the adoption of new content.