Exploring Image Virality in Google Plus

Abstract

Reactions to posts in an online social network show different dynamics depending on several textual features of the corresponding content. Do similar dynamics exist when images are posted? Exploiting a novel dataset of posts, gathered from the most popular Google+ users, we try to give an answer to such a question. We describe several virality phenomena that emerge when taking into account visual characteristics of images (such as orientation, mean saturation, etc.). We also provide hypotheses and potential explanations for the dynamics behind them, and include cases for which common-sense expectations do not hold true in our experiments.

8 pages, 8 figures. IEEE/ASE SocialCom 2013

References in corpus (2)

• Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers
• You had me at hello: How phrasing affects memorability

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• Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks
• On the Virality of Animated GIFs on Tumblr