Characterizing popularity dynamics of online videos
- Ren, Zhuo-Ming Department of Physics, University of Fribourg, Switzerland
- Shi, Yu-Qiang School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Mianyang, China
- Liao, Hao Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, China - Department of Physics, University of Fribourg, Switzerland
-
01.07.2016
Published in:
- Physica A: Statistical Mechanics and its Applications. - 2016, vol. 453, p. 236–241
English
Online popularity has a major impact on videos, music, news and other contexts in online systems. Characterizing online popularity dynamics is nature to explain the observed properties in terms of the already acquired popularity of each individual. In this paper, we provide a quantitative, large scale, temporal analysis of the popularity dynamics in two online video-provided websites, namely MovieLens and Netflix. The two collected data sets contain over 100 million records and even span a decade. We characterize that the popularity dynamics of online videos evolve over time, and find that the dynamics of the online video popularity can be characterized by the burst behaviors, typically occurring in the early life span of a video, and later restricting to the classic preferential popularity increase mechanism.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
-
- English
- Classification
- Physics
- License
- License undefined
- Identifiers
-
- RERO DOC 261174
- DOI 10.1016/j.physa.2016.02.019
- Persistent URL
- https://folia.unifr.ch/unifr/documents/304905
Statistics
Document views: 52
File downloads:
- ren_cpd.pdf: 113