TY - JOUR
T1 - Characterizing and modeling user behavior in a large-scale mobile live streaming system
AU - Li, Zhenyu
AU - Kaafar, Mohamed Ali
AU - Salamatian, Kave
AU - Xie, Gaogang
PY - 2017/12/1
Y1 - 2017/12/1
N2 - In mobile live streaming systems, users have fairly limited interactions with streaming objects due to the constraints coming from mobile devices and the event-driven nature of live content. The constraints could lead to unique user behavior characteristics, which have yet to be explored. This paper investigates over 9 million access logs collected from the PPTV live streaming system, with an emphasis on the discrepancies that might exist when users access the live streaming catalog from mobile and nonmobile terminals. We observe a much higher likelihood of abandoning sessions by mobile users and examine the structure of abandoned sessions from the perspectives of time of day, channel content, and mobile device types. Surprisingly, we find relatively low abandonment rates during peak-load time periods and a notable impact of mobile device type (i.e., Android or iOS) on the abandonment behavior. To further capture the intrinsic characteristics of user behavior, we develop a series of models for session duration, user activity, and time dynamics of user arrivals/departures. More importantly, we relate the model parameters to physical and real-life meanings. The observations and models shed light on a video delivery system, telco-content delivery networks, and mobile applications.
AB - In mobile live streaming systems, users have fairly limited interactions with streaming objects due to the constraints coming from mobile devices and the event-driven nature of live content. The constraints could lead to unique user behavior characteristics, which have yet to be explored. This paper investigates over 9 million access logs collected from the PPTV live streaming system, with an emphasis on the discrepancies that might exist when users access the live streaming catalog from mobile and nonmobile terminals. We observe a much higher likelihood of abandoning sessions by mobile users and examine the structure of abandoned sessions from the perspectives of time of day, channel content, and mobile device types. Surprisingly, we find relatively low abandonment rates during peak-load time periods and a notable impact of mobile device type (i.e., Android or iOS) on the abandonment behavior. To further capture the intrinsic characteristics of user behavior, we develop a series of models for session duration, user activity, and time dynamics of user arrivals/departures. More importantly, we relate the model parameters to physical and real-life meanings. The observations and models shed light on a video delivery system, telco-content delivery networks, and mobile applications.
KW - Analysis
KW - mobile live streaming
KW - modeling
KW - user behavior
UR - http://www.scopus.com/inward/record.url?scp=85040904211&partnerID=8YFLogxK
U2 - 10.1109/TCSVT.2016.2595325
DO - 10.1109/TCSVT.2016.2595325
M3 - Article
AN - SCOPUS:85040904211
SN - 1051-8215
VL - 27
SP - 2675
EP - 2686
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 12
ER -