Unveiling the Patterns of Video Tweeting: A Sina Weibo-based Measurement Study
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1 Unveiling the Patterns of Video Tweeting: A Sina Weibo-based Measurement Study Zhida Guo 1, Jian Huang 1, Jian He 1, Xiaojun Hei 2, and Di Wu 1. 1 Sun Yat-sen University, China 2 Huazhong University of Sci. & Tech., China
2 Outline Introduction Methodology Measurement Results Conclusion 2
3 Introduction Sina Weibo More than 300 million users Most popular Twitter-like microblog service in China Contributions of our paper: Investigate the patterns of video tweeting Guide the design of future microblog-oriented video distribution platforms Video Tweet, A tweet that contains a video link 3
4 Outline Introduction Methodology Measurement Results Conclusion 4
5 Measurement Infrastructure 5
6 Tasks Generate User Identities(UIDs) Collect video tweets UID: <=12 digits Uniformly sampling in ID space (generate random UIDs and check their validness) 5 days to get a user set with one million users Weibo API limitation: 150 queries/hour/account/app/ip 1000 queries/app Register 40 apps & 15 accounts Auto switch when quota is exhausted Crawl comments and retweets Get videos information 6
7 Data Set Root video tweet: directly posted by a user himself 245,135 video tweets (original and retweeted ) (from to ) Remove duplicated, 0-retweeted and unavailable ones 87,699 root video tweets (Data Set 1) Randomly select from Data Set 1 6,500 root video tweets (Data Set 2) 7
8 Outline Introduction Methodology Measurement Results Statistics of Tweeted Videos Viewer Behavior Characteristics Effects of Social Links Conclusion 8
9 Statistics of tweeted Videos # of tweeted videos: Tudou > Youku Contrast to real market Youku (39.1%) Tudou (20.3%) Fig.1. Video source distribution Market Share Remarks: Collaboration between Tudou and Sina: users can upload videos to Tudou via Weibo Interface directly 9
10 Statistics of tweeted videos (cont.) Short videos: 80% <= 10 min Observation: Fig.2. Video length distribution Short video clips are common 10
11 Statistics of tweeted videos (cont.) 1.6% videos have more than 10,000 views 85% videos have less 1,000 views Estimate the popularity : sum of retweets and comments 6,500 video tweets: 5.5 million views Observation: Long tail distribution 11 Fig.3. Popularity distribution of videos
12 Viewer Behavior Characteristics 3% : not internationalized Fig.4. Geographical distribution of viewers Top 3 region: Guangdong(35%),Beijing(7.6%),Shanghai(7.6%) 12
13 Viewer Behavior Characteristics (cont.) Mobile device views 32% v.s. PC views 68% 13 Fig.5. Distribution of user devices
14 Viewer Behavior Characteristics (cont.) Fig.6. Distribution of mobile clients Android phone(34.2%), iphone(32.7%), ipad(8%) 14
15 Viewer Behavior Characteristics (cont.) Flash crowd Fig.7. Popularity dynamics of Top 5 popular videos Frequent flash crowd, probably caused by social star's retweet/comment or system's recommendation 15
16 Viewer Behavior Characteristics (cont.) 87% 1-st view <= 1 hour 60% 1000-th view <= 1 day Observation: Fast spreading nature of microblog service 16 Fig.8. Time lag between the orginal video tweet and its n-th view
17 Viewer Behavior Characteristics (cont.) 93% <= 3 50-active periods 49% no 50-active period k-active period: consecutive time slots(1 hour) each of which contains at least k views 17 Fig.9. Number of active periods
18 Viewer Behavior Characteristics (cont.) Over 90% <= 10 hours Over 50% <= 1 hour 18 Fig.10. Duration of active periods Observation: The popularity of tweeted videos can not last for a long period
19 Effects of Social Links Percentage: 93.5% 98% within 3 hops Propagation Distance: # of social hops between orginal tweet publisher and the tweet viewer 19 (a) Propagation distance of all viewers (b) Propagation distance for videos with different popularities Fig.11.. Distribution of propagation distance
20 Outline Introduction Methodology Measurement Results Conclusion 20
21 Conclusion Short Videos (80%<=10 min) Flash Crowds (87% 1-st view <= one hour) &Short Popular Time (Over 90% <= 10 hours) Video tweeting over the Sina Weibo System Effects of Social Links Propagation Distance <=3 21
22 Discussion and Future Work How to design future microblog-oriented video distribution platform? Short Video Length User Generated Contents Video Prefetching Small Propagation Distance Microblogoriented Video Distribution Platform Diverse User Devices Real-Time Transcoding Online Bandwidth Provisioning Frequent Flash Crowds 22
23 Q&A Thanks! Zhida Guo 1, Jian Huang 1, Jian He 1, Xiaojun Hei 2, and Di Wu 1. 1 Sun Yat-sen University, China 2 Huazhong University of Sci. & Tech., China 23
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