Analyzing User Activities, Demographics, Social Network Structure and User-Generated Content on Instagram

TL;DR

This paper provides the first comprehensive large-scale analysis of Instagram, revealing unique social network properties, user activity patterns, and content sharing behaviors, based on data collected over one month.

Contribution

It offers novel insights into Instagram's social network structure, user activity frequency, and location sharing habits, filling a research gap on this popular platform.

Findings

Instagram's social network differs from Twitter and Flickr

Users typically post once a week

Users frequently share locations with friends

Abstract

Instagram is a relatively new form of communication where users can instantly share their current status by taking pictures and tweaking them using filters. It has seen a rapid growth in the number of users as well as uploads since it was launched in October 2010. Inspite of the fact that it is the most popular photo sharing application, it has attracted relatively less attention from the web and social media research community. In this paper, we present a large-scale quantitative analysis on millions of users and pictures we crawled over 1 month from Instagram. Our analysis reveals several insights on Instagram which were never studied before: 1) its social network properties are quite different from other popular social media like Twitter and Flickr, 2) people typically post once a week, and 3) people like to share their locations with friends. To the best of our knowledge, this is the first in-depth analysis of user activities, demographics, social network structure and user-generated content on Instagram.