Name
Abstract | ||
|---|---|---|
Mobile personal livecast (MPL) services are emerging and have received great attention recently. Unlike traditional livecast services with commercial content providers (e.g., live TV), the live contents in MPL are crowdsourced from and consumed among geo-distributed individuals. Although there exist typical social relationships in MPL (i.e., follower-followee), different from conventional social networking services like Twitter and Facebook, which have much of a tolerance for interaction delay, the interactions in MPL must be in real-time. These unique characteristics intrigue us to investigate how the relationships (e.g., social links and geo-locations) between viewers and broadcasters influence the user behaviors, which has yet to be explored in depth. In this paper, we carry out extensive measurements of Inke, one of the most popular MPL providers, with a large-scale dataset containing 11M users. Our key findings are as follows. First, compared with traditional livecast services, the user interests shift much more frequently and the average viewing duration is considerably shorter in MPL. Second, the existence of social relationships significantly strengthens viewer stickiness-followers dedicating longer viewing time (contributing 81% of the total viewing time) and being 2x more patient when suffering poor network connectivity than non-followers. Third, most of the broadcasts in MPL are geographically local-popular (the majority of the views come from the same region of the broadcaster). Based on these critical observations, we provide insights that can enhance the MPL system design from the perspectives of efficient resource allocation and envision a future MPL framework that collaboratively utilizes the cloud and edge computing resources to improve efficiency and scalability for Inke-like services. © 2017 ACM. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3083165.3083169 | Proceedings of the 27th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2017 |
Keywords | Field | DocType |
Mobile personal livecast,User behavior analysis | Edge computing,Network connectivity,Social relationship,World Wide Web,Social network,Computer science,Systems design,Resource allocation,Scalability,Cloud computing | Conference |
ISBN | Citations | PageRank |
9781450350037 | 4 | 0.42 |
References | Authors | |
13 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ming Ma | 1 | 87 | 15.25 |
| Lei Zhang | 2 | 59 | 4.89 |
| Jiangchuan Liu | 3 | 4340 | 310.86 |
| Wang Zhi | 4 | 461 | 51.72 |
| Li Weihua | 5 | 4 | 0.42 |
| Hou Guangling | 6 | 4 | 0.42 |
| Lifeng Sun | 7 | 967 | 98.43 |