Spatial popularity and similarity of watching videos in large-scale urban environment
Spatial popularity and similarity of watching videos in large-scale urban environment
With the popularity of watching mobile videos, a major form of multimedia contents, many works focus on the geographic features of user viewing behaviors, but few study them in the context of an entire metropolitan city. Different regions of a large city have different intensity of economy activities with respect to their different distances to the downtown, and how this will influence video popularity and similarity is still unclear. To quantitatively study the spatial popularity and similarity of watching videos in a large urban environment, we collect a dataset with two-month video view requests from the largest network provider in Shanghai, containing top six content providers, and study the spatial features of video access in regions of different scales. We find that 1) video popularity and similarity exist at different scales of city division; 2) the concentration of video popularity becomes higher as the region is closer to downtown; 3) when comparing the regions of same scale, the similarity of popular videos becomes lower as the region is farther away from the downtown. Finally, we correlate our findings with cache deployment, advertising and video recommendation to illustrate the implications.
city division., Logic gates, Motion pictures, Multimedia communication, Streaming media, TV, Urban areas, urban computing, Video spatial popularity, video spatial similarity, Videos
797-810
Yan, Huan
da178da6-e9c3-440e-a339-ede416b6d14a
Liu, Jiaqiang
abca929c-5011-4457-aadf-fa10165c940f
Li, Yong
ac705db5-b891-4d14-ac43-a87acd05cdd7
Jin, Depeng
8fd076c0-8da5-47d1-ac9e-9dacd3f27c83
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Yan, Huan
da178da6-e9c3-440e-a339-ede416b6d14a
Liu, Jiaqiang
abca929c-5011-4457-aadf-fa10165c940f
Li, Yong
ac705db5-b891-4d14-ac43-a87acd05cdd7
Jin, Depeng
8fd076c0-8da5-47d1-ac9e-9dacd3f27c83
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Yan, Huan, Liu, Jiaqiang, Li, Yong, Jin, Depeng and Chen, Sheng
(2018)
Spatial popularity and similarity of watching videos in large-scale urban environment.
IEEE Transactions on Network and Service Management, 15 (2), .
(doi:10.1109/TNSM.2018.2817549).
Abstract
With the popularity of watching mobile videos, a major form of multimedia contents, many works focus on the geographic features of user viewing behaviors, but few study them in the context of an entire metropolitan city. Different regions of a large city have different intensity of economy activities with respect to their different distances to the downtown, and how this will influence video popularity and similarity is still unclear. To quantitatively study the spatial popularity and similarity of watching videos in a large urban environment, we collect a dataset with two-month video view requests from the largest network provider in Shanghai, containing top six content providers, and study the spatial features of video access in regions of different scales. We find that 1) video popularity and similarity exist at different scales of city division; 2) the concentration of video popularity becomes higher as the region is closer to downtown; 3) when comparing the regions of same scale, the similarity of popular videos becomes lower as the region is farther away from the downtown. Finally, we correlate our findings with cache deployment, advertising and video recommendation to illustrate the implications.
Text
Spatial Popularity and Similarity of Watching Videos in Large-scale Urban Environment
- Accepted Manuscript
More information
Accepted/In Press date: 19 March 2018
e-pub ahead of print date: 20 March 2018
Additional Information:
AM added 24/4/18
Keywords:
city division., Logic gates, Motion pictures, Multimedia communication, Streaming media, TV, Urban areas, urban computing, Video spatial popularity, video spatial similarity, Videos
Identifiers
Local EPrints ID: 419956
URI: http://eprints.soton.ac.uk/id/eprint/419956
ISSN: 1932-4537
PURE UUID: b386fafc-fb90-42fe-b509-355a9b2f5615
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Date deposited: 24 Apr 2018 16:30
Last modified: 15 Mar 2024 19:22
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Contributors
Author:
Huan Yan
Author:
Jiaqiang Liu
Author:
Yong Li
Author:
Depeng Jin
Author:
Sheng Chen
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