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

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arxiv 1410.8099 v1 pith:AVHYPN7Y submitted 2014-10-29 cs.SI physics.soc-ph

classification cs.SIphysics.soc-ph
keywords instagramsocialanalysisnetworkusersactivitiescontentdemographics
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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    Meta-PO transfers prior users' preference models through weighted Bayesian optimization, helping new users find desired image or lighting appearances in about 4 to 8 iterations instead of 7 to 10.

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