Abstract
This article characterizes video-based interactions that emerge from YouTube's video response feature, which allows users to discuss themes and to provide reviews for products or places using much richer media than text. Based on crawled data covering a representative subset of videos and users, we present a characterization from two perspectives: the video response view and the interaction network view. In addition to providing valuable statistical models for various characteristics, our study uncovers typical user behavioral patterns in video-based environments and shows evidence of opportunistic behavior.
- Albert, R., Jeong, H., and Barabasi, A. 1999. The diameter of the World Wide Web. Nature 401, 130--131.Google Scholar
Cross Ref
- Almeida, V., Bestavros, A., Crovella, M., and Oliveira, A. 1996. Characterizing reference locality in the WWW. In Proceedings of the International Conference on Parallel and Distributed Information Systems (PDIS'96). Google Scholar
Digital Library
- Barford, P. and Crovella, M. 1998. Generating representative Web workloads for network and server performance evaluation. SIGMETRICS Perform. Eval. Rev. 26, 1, 151--160. Google Scholar
Digital Library
- Benevenuto, F., Duarte, F., Rodrigues, T., Almeida, V., Almeida, J., and Ross, K. 2008a. Understanding video interactions in Youtube. In Proceedings of the ACM International Conference on Multimedia (MM). Google Scholar
Digital Library
- Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., and Gonalves, M. 2009a. Detecting spammers and content promoters in online video social networks. In Proceedings of the International ACM SIGIR Conference. Google Scholar
Digital Library
- Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., Zhang, C., and Ross, K. 2008b. Identifying video spammers in online social networks. In Proceedings of the International Workshop on Adversarial Information Retrieval on the Web (AIRWeb). Google Scholar
Digital Library
- Benevenuto, F., Rodrigues, T., Cha, M., and Almeida, V. 2009b. Characterizing user behavior in online social networks. In Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC). Google Scholar
Digital Library
- Boll, S. 2007. Multitube--where Web 2.0 and multimedia could meet. IEEE MultiMedia 14, 1, 9--13. Google Scholar
Digital Library
- Breslau, L., Cao, P., Fan, L., Phillips, G., and Shenker, S. 1999. Web Caching and Zipf-like Distributions: Evidence and Implications. In Proceedings of IEEE Infocom.Google Scholar
- Brin, S. and Page, L. 1998. The anatomy of a large-scale hypertextual Web search engine. Comput. Netw. ISDN Syst. 30, 1--7, 107--117. Google Scholar
Digital Library
- Broder, A., Kumar, R., Maghoul, F., Raghavan, P., Rajagopalan, S., Stata, R., Tomkins, A., and Wiener, J. 2000a. Graph structure in the Web. Comput. Netw. 33, 1--6, 309--320. Google Scholar
Digital Library
- Broder, A., Kumar, R., Maghoul, F., Raghavan, P., Rajagopalan, S., Stata, R., Tomkins, A., and Wiener, J. 2000b. Graph structure in the Web: Experiments and models. In Proceedings of the International World Wide Web Conference (WWW). Google Scholar
Digital Library
- Cha, M., Kwak, H., Rodriguez, P., Ahn, Y., and Moon, S. 2007. I tube, you tube, everybody tubes: Analyzing the world's largest user generated content video system. In Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC). Google Scholar
Digital Library
- Chau, D., Pandit, Wang, S., and Faloutsos, C. 2007. Parallel crawling for online social networks. In Proceedings of the International World Wide Web Conference (WWW). Google Scholar
Digital Library
- Choudhury, M., Sundaram, H., John, A., and Seligmann, D. 2009. What makes conversations interesting? themes, participants and consequences of conversations in online social media. In Proceedings of the International World Wide Web Conference (WWW). Google Scholar
Digital Library
- Chua, T.-S., Tang, J., Hong, R., Li, H., Luo, Z., and Zheng, Y.-T. 2009. Nus-wide: A real-world Web image database from National University of Singapore. In Proceedings of the ACM Conference on Image and Video Retrieval (CIVR'09). Google Scholar
Digital Library
- Chun, H., Kwak, H., Eom, Y., Ahn, Y., Moon, S., and Jeong, H. 2008. Comparison of online social relations in volume vs interaction: A case study of cyworld. In Proceedings of the ACM SIGCOMM Conference on Internet Measurement (IMC). Google Scholar
Digital Library
- Duarte, F., Mattos, B., Almeida, J., Almeida, V., Curiel, M., and Bestavros, A. 2008. Hierarchical characterization and generation of blogosphere workloads. Tech. rep., Computer Science Department, Boston University.Google Scholar
- Ebel, H., Mielsch, L., and Bornholdt, S. 2002. Scale free topology of e-mail networks. Phys. Rev. E 035103.Google Scholar
Cross Ref
- Garlaschelli, D. and Loffredo, M. 2004. Patterns of link reciprocity in directed networks. Phys. Rev. Lett. 93.Google Scholar
Cross Ref
- Gill, P., Arlitt, M., Li, Z., and Mahanti, A. 2007. Youtube traffic characterization: A view from the edge. In Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC). Google Scholar
Digital Library
- Golder, S., Wilkinson, D., and Huberman, B. 2007. Rhythms of social interaction: Messaging within a massive online network. Proceedings of the International Conference on Communities and Technologies.Google Scholar
- Gomes, L., Almeida, J., Almeida, V., and Meira, W. 2007. Workload models of spam and legitimate e-mails. Perform. Eval. 64, 7-8, 690--714. Google Scholar
Digital Library
- Gómez, V., Kaltenbrunner, A., and López, V. 2008. Statistical analysis of the social network and discussion threads in slashdot. In Proceedings of the International Conference on World Wide Web (WWW). Google Scholar
Digital Library
- Heymann, P., Koutrika, G., and Garcia-Molina, H. 2007. Fighting spam on social Web sites: A survey of approaches and future challenges. IEEE Internet Comput. 11. Google Scholar
Digital Library
- Huberman, B., Romero, D., and Wu, F. 2009. Social networks that matter: Twitter under the microscope. First Monday 14, 1.Google Scholar
- Jain, R. 1991. The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. John Wiley and Sons.Google Scholar
- Java, A., Song, X., Finin, T., and Tseng, B. 2007. Why we Twitter: Understanding microblogging usage and communities. In Proceedings of the Workshop on Web Mining and social network analysis (WebKDD/SNA-KDD). Google Scholar
Digital Library
- Kleinberg, J. 1999. Hubs, authorities, and communities. ACM Comput. Surv. 31, 5. Google Scholar
Digital Library
- Krishnamurthy, B., Gill, P., and Arlitt, M. 2008. A few chirps about Twitter. In Proceedings of the ACM SIGCOMM Workshop on Social Networks (WOSN). Google Scholar
Digital Library
- Kumar, R., Novak, J., Raghavan, P., and Tomkins, A. 2003. On the bursty evolution of blogspace. In Proceedings of the International World Wide Web Conference (WWW). Google Scholar
Digital Library
- Leskovec, J. and Horvitz, E. 2008. Planetary-scale views on a large instant-messaging network. In Proceedings of the International Conference on World Wide Web (WWW). Google Scholar
Digital Library
- Liben-Nowell, D., Novak, J., Kumar, R., Raghavan, P., and Tomkins, A. 2005. Geographic routing in social network. In Proc. Nat. Aca. Sci.Google Scholar
- Mislove, A., Marcon, M., Gummadi, K., Druschel, P., and Bhattacharjee, B. 2007. Measurement and analysis of online social networks. In Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC). Google Scholar
Digital Library
- Newman, M. 2002. Assortative mixing in networks. Phys. Rev. Lett. 89.Google Scholar
Cross Ref
- Newman, M. and Park, J. 2003. Why social networks are different from other types of networks. Phys. Rev. E 68.Google Scholar
Cross Ref
- Onnela, J., Saramäki, J., Hyvönen, J., Szabó, G., Menezes, A., Kaski, K., Barabási, A., and Kertész, J. 2007. Analysis of a large-scale weighted network of one-to-one human communication. New J. Phys. 9, 6 (June).Google Scholar
Cross Ref
- Pandurangan, G., Raghavan, P., and Upfal, E. 2002. Using Pagerank to characterize Web structure. In Proceedings of the International Conference on Computing and Combinatorics (COCOON). Google Scholar
Digital Library
- Ross, K. 2003. Asynchronous voice: A personal account. Proceedings of the IEEE Multimedia 10, 2, 70--74. Google Scholar
Digital Library
- Seshadri, M., Machiraju, S., Sridharan, A., Bolot, J., Faloutsos, C., and Leskove, J. 2008. Mobile call graphs: Beyond power-law and lognormal distributions. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). Google Scholar
Digital Library
- Shannon, M. 2007. Shaking hands, kissing babies, and … blogging? Commun. ACM 50. Google Scholar
Digital Library
- Trivedi, K. S. 2002. Probability and Statistics with Reliability, Queuing and Computer Science Applications. Prentice-Hall. Google Scholar
Digital Library
- Zhang, J., Ackerman, M., and Adamic, L. 2007. Expertise networks in online communities: Structure and algorithms. In Proceedings of the International World Wide Web Conference (WWW). Google Scholar
Digital Library
- Zink, M., Suh, K., Gu, Y., and Kurose, J. 2008. Watch global, cache local: Youtube network traces at a campus network—measurements and implications. In Proceedings of the IEEE Multimedia Computing and Networking (MMCN).Google Scholar
- Zinman, A. and Donath, J. 2007. Is Britney Spears spam? In Proceedings of the Conference on Email and Anti-Spam (CEAS).Google Scholar
- Zlatic, V., Bozicevic, M., Stefancic, H., and Domazet, M. 2006. Wikipedias: Collaborative Web-based encyclopedias as complex networks. Phys. Rev. E 74, 1.Google Scholar
Cross Ref
Index Terms
Video interactions in online video social networks
Recommendations
Understanding video interactions in youtube
MM '08: Proceedings of the 16th ACM international conference on MultimediaThis paper seeks understanding the user behavior in a social network created essentially by video interactions. We present a characterization of a social network created by the video interactions among users on YouTube, a popular social networking video ...
Trends in Social Media Usage: An Investigation of its Growth in the Arab World
In the present era of Web 2.0 and Web 3.0, Social Networking Sites have given us means of providing real-time services. Recent years have brought a massive growth in the social networking phenomenon. The use of social media in the Arab World has been ...
The impact of network structure on breaking ties in online social networks: unfollowing on twitter
CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsWe investigate the breaking of ties between individuals in the online social network of Twitter, a hugely popular social media service. Building on sociology concepts such as strength of ties, embeddedness, and status, we explore how network structure ...






Comments