TY - GEN
T1 - User churn in focused question answering sites
T2 - 23rd International Conference on World Wide Web, WWW 2014
AU - Pudipeddi, Jagat
AU - Akoglu, Leman
AU - Tong, Hanghang
N1 - Funding Information:
We thank the reviewers for helping us improve our manuscript. This material is based on work supported by the Army Research Office under Contract No. W911NF-14-1-0029 and Stony Brook University Office of Vice President for Research. Any findings and conclusions expressed in this material are those of the author(s) and do not necessarily reect the views of the funding parties.
Publisher Copyright:
© Copyright 2014 by the International World Wide Web Conferences Steering Committee.
PY - 2014/4/7
Y1 - 2014/4/7
N2 - Given a user on a Q&A site, how can we tell whether s/he is engaged with the site or is rather likely to leave? What are the most evidential factors that relate to users churning? Question and Answer (Q&A) sites form excellent repos- itories of collective knowledge. To make these sites self- sustainable and long-lasting, it is crucial to ensure that new users as well as the site veterans who provide most of the answers keep engaged with the site. As such, quantifying the engagement of users and preventing churn in Q&A sites are vital to improve the lifespan of these sites. We study a large data collection from stackoverflow.com to identify significant factors that correlate with newcomer user churn in the early stage and those that relate to veterans leaving in the later stage. We consider the problem under two settings: given (i) the first k posts, or (ii) first T days of activity of a user, we aim to identify evidential features to automatically classify users so as to spot those who are about to leave. We find that in both cases, the time gap between subsequent posts is the most significant indicator of diminishing interest of users, besides other indicative factors like answering speed, reputation of those who answer their questions, and number of answers received by the user.
AB - Given a user on a Q&A site, how can we tell whether s/he is engaged with the site or is rather likely to leave? What are the most evidential factors that relate to users churning? Question and Answer (Q&A) sites form excellent repos- itories of collective knowledge. To make these sites self- sustainable and long-lasting, it is crucial to ensure that new users as well as the site veterans who provide most of the answers keep engaged with the site. As such, quantifying the engagement of users and preventing churn in Q&A sites are vital to improve the lifespan of these sites. We study a large data collection from stackoverflow.com to identify significant factors that correlate with newcomer user churn in the early stage and those that relate to veterans leaving in the later stage. We consider the problem under two settings: given (i) the first k posts, or (ii) first T days of activity of a user, we aim to identify evidential features to automatically classify users so as to spot those who are about to leave. We find that in both cases, the time gap between subsequent posts is the most significant indicator of diminishing interest of users, besides other indicative factors like answering speed, reputation of those who answer their questions, and number of answers received by the user.
KW - Churn prediction
KW - Feature extraction
KW - Q and A sites
KW - User churn
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U2 - 10.1145/2567948.2576965
DO - 10.1145/2567948.2576965
M3 - Conference contribution
AN - SCOPUS:84963536064
T3 - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
SP - 469
EP - 474
BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PB - Association for Computing Machinery
Y2 - 7 April 2014 through 11 April 2014
ER -