Online Popularity and Topical Interests through the Lens of Instagram
Emilio Ferrara, Roberto Interdonato, Andrea Tagarelli

TL;DR
This paper analyzes Instagram to understand user behavior, content popularity, and community formation by examining network structure, content dynamics, and tagging behavior, revealing how trends and interests emerge from individual actions.
Contribution
It provides a comprehensive analysis of Instagram's social network, content dynamics, and tagging behavior, offering new insights into online popularity and topical interests.
Findings
Identification of community structures based on topical interests.
Insights into how global trends and popular users emerge.
Understanding of user attention and topical diversity through tagging behavior.
Abstract
Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to gathering hundred millions users. Instagram exhibits a mixture of features including social structure, social tagging and media sharing. The network of social interactions among users models various dynamics including follower/followee relations and users' communication by means of posts/comments. Users can upload and tag media such as photos and pictures, and they can "like" and comment each piece of information on the platform. In this work we investigate three major aspects on our Instagram dataset: (i) the structural characteristics of its network of heterogeneous interactions, to unveil the emergence of self organization and topically-induced…
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