{"title":"YouTube直播和Twitch:用户生成的直播系统之旅","authors":"Karine Pires, G. Simon","doi":"10.1145/2713168.2713195","DOIUrl":null,"url":null,"abstract":"User-Generated live video streaming systems are services that allow anybody to broadcast a video stream over the Internet. These Over-The-Top services have recently gained popularity, in particular with e-sport, and can now be seen as competitors of the traditional cable TV. In this paper, we present a dataset for further works on these systems. This dataset contains data on the two main user-generated live streaming systems: Twitch and the live service of YouTube. We got three months of traces of these services from January to April 2014. Our dataset includes, at every five minutes, the identifier of the online broadcaster, the number of people watching the stream, and various other media information. In this paper, we introduce the dataset and we make a preliminary study to show the size of the dataset and its potentials. We first show that both systems generate a significant traffic with frequent peaks at more than 1 Tbps. Thanks to more than a million unique uploaders, Twitch is in particular able to offer a rich service at anytime. Our second main observation is that the popularity of these channels is more heterogeneous than what have been observed in other services gathering user-generated content.","PeriodicalId":202494,"journal":{"name":"Proceedings of the 6th ACM Multimedia Systems Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"192","resultStr":"{\"title\":\"YouTube live and Twitch: a tour of user-generated live streaming systems\",\"authors\":\"Karine Pires, G. Simon\",\"doi\":\"10.1145/2713168.2713195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"User-Generated live video streaming systems are services that allow anybody to broadcast a video stream over the Internet. These Over-The-Top services have recently gained popularity, in particular with e-sport, and can now be seen as competitors of the traditional cable TV. In this paper, we present a dataset for further works on these systems. This dataset contains data on the two main user-generated live streaming systems: Twitch and the live service of YouTube. We got three months of traces of these services from January to April 2014. Our dataset includes, at every five minutes, the identifier of the online broadcaster, the number of people watching the stream, and various other media information. In this paper, we introduce the dataset and we make a preliminary study to show the size of the dataset and its potentials. We first show that both systems generate a significant traffic with frequent peaks at more than 1 Tbps. Thanks to more than a million unique uploaders, Twitch is in particular able to offer a rich service at anytime. Our second main observation is that the popularity of these channels is more heterogeneous than what have been observed in other services gathering user-generated content.\",\"PeriodicalId\":202494,\"journal\":{\"name\":\"Proceedings of the 6th ACM Multimedia Systems Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"192\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th ACM Multimedia Systems Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2713168.2713195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th ACM Multimedia Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2713168.2713195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
YouTube live and Twitch: a tour of user-generated live streaming systems
User-Generated live video streaming systems are services that allow anybody to broadcast a video stream over the Internet. These Over-The-Top services have recently gained popularity, in particular with e-sport, and can now be seen as competitors of the traditional cable TV. In this paper, we present a dataset for further works on these systems. This dataset contains data on the two main user-generated live streaming systems: Twitch and the live service of YouTube. We got three months of traces of these services from January to April 2014. Our dataset includes, at every five minutes, the identifier of the online broadcaster, the number of people watching the stream, and various other media information. In this paper, we introduce the dataset and we make a preliminary study to show the size of the dataset and its potentials. We first show that both systems generate a significant traffic with frequent peaks at more than 1 Tbps. Thanks to more than a million unique uploaders, Twitch is in particular able to offer a rich service at anytime. Our second main observation is that the popularity of these channels is more heterogeneous than what have been observed in other services gathering user-generated content.
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