TY - GEN
T1 - On migratory behavior in video consumption
AU - Yan, Huan
AU - Lin, Tzu Heng
AU - Wang, Gang
AU - Li, Yong
AU - Zheng, Haitao
AU - Jin, Depeng
AU - Zhao, Ben Y.
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/11/6
Y1 - 2017/11/6
N2 - Today's video streaming market is crowded with various content providers (CPs). For individual CPs, understanding user behavior, in particular how users migrate among different CPs, is crucial for improving users' on-site experience and the CP's chance of success. In this paper, we take a data-driven approach to analyze and model user migration behavior in video streaming, i.e., users switching content provider during active sessions. Based on a large ISP dataset over two months (6 major content providers, 3.8 million users, and 315 million video requests), we study common migration patterns and reasons of migration.We find that migratory behavior is prevalent: 66% of users switch CPs with an average switching frequency of 13%. In addition, migration behaviors are highly diverse: regardless large or small CPs, they all have dedicated groups of users who like to switch to them for certain types of videos. Regarding reasons of migration, we find CP service quality rarely causes migration, while a few popular videos play a bigger role. Nearly 60% of cross-site migrations are landed to 0.14% top videos. Finally, we validate our findings by building an accurate regression model to predict user migration frequency, and discuss the implications of our results to CPs.
AB - Today's video streaming market is crowded with various content providers (CPs). For individual CPs, understanding user behavior, in particular how users migrate among different CPs, is crucial for improving users' on-site experience and the CP's chance of success. In this paper, we take a data-driven approach to analyze and model user migration behavior in video streaming, i.e., users switching content provider during active sessions. Based on a large ISP dataset over two months (6 major content providers, 3.8 million users, and 315 million video requests), we study common migration patterns and reasons of migration.We find that migratory behavior is prevalent: 66% of users switch CPs with an average switching frequency of 13%. In addition, migration behaviors are highly diverse: regardless large or small CPs, they all have dedicated groups of users who like to switch to them for certain types of videos. Regarding reasons of migration, we find CP service quality rarely causes migration, while a few popular videos play a bigger role. Nearly 60% of cross-site migrations are landed to 0.14% top videos. Finally, we validate our findings by building an accurate regression model to predict user migration frequency, and discuss the implications of our results to CPs.
KW - Migratory behavior
KW - Video consumption
UR - http://www.scopus.com/inward/record.url?scp=85037369220&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85037369220&partnerID=8YFLogxK
U2 - 10.1145/3132847.3132884
DO - 10.1145/3132847.3132884
M3 - Conference contribution
AN - SCOPUS:85037369220
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1109
EP - 1118
BT - CIKM 2017 - Proceedings of the 2017 ACM Conference on Information and Knowledge Management
PB - Association for Computing Machinery
T2 - 26th ACM International Conference on Information and Knowledge Management, CIKM 2017
Y2 - 6 November 2017 through 10 November 2017
ER -