Viral content propagation in Online Social Networks

TL;DR

This paper analyzes how information spreads in online social networks, identifying patterns of virality across platforms like Reddit, Twitter, and Facebook, and highlighting the influence of content positivity and data access limitations.

Contribution

It introduces a multi-platform diffusion analysis of viral content, revealing key factors affecting virality and discussing data access challenges in OSN research.

Findings

Positive content has higher virality probability

Overall user-generated content has low virality probability

Different diffusion patterns are observed across platforms

Abstract

Information flows are the result of a constant exchange in Online Social Networks (OSNs). OSN users create and share varying types of information in real-time throughout a day. Virality is introduced as a term to describe information that reaches a wide audience within a small time-frame. As a case, we measure propagation of information submitted in Reddit, identify different patterns and present a multi OSN diffusion analysis on Twitter, Facebook, and 2 hosting domains for images and multimedia, ImgUr and YouTube. Our results indicate that positive content is the most shared and presents the highest virality probability, and the overall virality probability of user created information is low. Finally, we underline the problems of limited access in OSN data. Keywords: Online Social Networks, Virality, Diffusion, Viral Content, Reddit, Twitter, Facebook, ImgUr, YouTube