Understanding User Behavior at Scale in a Mobile Video Chat Application

Lei Tian, Shaosong Li, Junho Ahn, David Chu, Richard Han, Qin Lv, and Shivakant Mishra

Abstract

Online video chat services such as Chatroulette and Omegle randomly match

users in video chat sessions and have become increasingly popular, with

tens of thousands of users online at anytime during a day. Our interest is in

examining user behavior in the growing domain of mobile video, and in

particular how users behave in such video chat services as they are

extended onto mobile clients. To date, over four thousand people have downloaded

and used our Android-based mobile client, which was developed to be compatible

with an existing video chat service. The paper provides

a first-ever detailed large scale study of mobile user behavior in a random video chat

service over a three week period. This study identifies major characteristics such as mobile user session durations, time of use, demographic distribution and the large number of brief sessions that

users click through to find good matches. Through content analysis of video and audio, as well as analysis of texting and clicking behavior, we discover key correlations among these characteristics, e.g., normal mobile users are highly correlated with using the front camera and with the presence of a face, whereas misbehaving mobile users have a high negative correlation with the presence of a face.

Details

Publication typeInproceedings
Published inUbiComp
PublisherACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2013)
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