Instagram is a relatively new form of communication where
users can easily share their updates by taking photos and
tweaking them using filters. It has seen rapid growth in the
number of users as well as uploads since it was launched in
October 2010. In spite of the fact that it is the most popular
photo capturing and sharing application, it has attracted relatively
less attention from the research community. In this
paper, we present both qualitative and quantitative analysis
on Instagram. We use computer vision techniques to examine
the photo content. Based on that, we identify the different
types of active users on Instagram using clustering. Our
results reveal several insights about Instagram which were
never studied before, that include: 1) Eight popular photos
categories, 2) Five distinct types of Instagram users in terms
of their posted photos, and 3) A user’s audience (number of
followers) is independent of his/her shared photos on Instagram.
To our knowledge, this is the first in-depth study of
content and users on Instagram.