Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Online social networking sites like MySpace, Facebook, and Flickr have become a popular way to share and disseminate content. Their massive popularity has led to viral marketing techniques that attempt to spread content, products, and ideas on these sites. However, there is little data publicly available on viral propagation in the real world and few studies have characterized how information spreads over current online social networks.

In this paper, we collect and analyze large-scale traces of information dissemination in the Flickr social network. Our analysis, based on crawls of the favorite markings of 2.5 million users on 11 million photos, aims at answering three key questions: (a) how widely does information propagate in the social network? (b) how quickly does information propagate? and (c) what is the role of word-of-mouth exchanges between friends in the overall propagation of information in the network? Contrary to viral marketing ``intuition,'' we find that (a) even popular photos do not spread widely throughout the network, (b) even popular photos spread slowly through the network, and (c) information exchanged between friends is likely to account for over 50 of all favorite-markings, but with a significant delay at each hop.

REFERENCES

• 1: Eytan Adar , Lada A. Adamic, Tracking Information Epidemics in Blogspace, Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, p.207-214, September 19-22, 2005 [doi>10.1109/WI.2005.151]
• 2: Aris Anagnostopoulos , Ravi Kumar , Mohammad Mahdian, Influence and correlation in social networks, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA [doi>10.1145/1401890.1401897]
• 3: Lars Backstrom , Dan Huttenlocher , Jon Kleinberg , Xiangyang Lan, Group formation in large social networks: membership, growth, and evolution, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, August 20-23, 2006, Philadelphia, PA, USA [doi>10.1145/1150402.1150412]
• 4: Bebra Aho Williamson. EMarketer Social Network Marketing: Ad Spending and Usage. 2007.
• 5: H. Chun, H. Kwak, Y.-H. Eom, Y.-Y. Ahn, S. Moon, and H. Jeong. Online Social Networks: Sheer Volume vs Social Interaction. In ACM IMC, 2008.
• 6: David Crandall , Dan Cosley , Daniel Huttenlocher , Jon Kleinberg , Siddharth Suri, Feedback effects between similarity and social influence in online communities, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA [doi>10.1145/1401890.1401914]
• 7: P. Dodds and D. Watts. A Generalized Model of Social and Biological Contagion. J. of Theoretical Biology, 2005.
• 8: Pedro Domingos , Matt Richardson, Mining the network value of customers, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, p.57-66, August 26-29, 2001, San Francisco, California [doi>10.1145/502512.502525]
• 9: Vicenç Gómez , Andreas Kaltenbrunner , Vicente López, Statistical analysis of the social network and discussion threads in slashdot, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China [doi>10.1145/1367497.1367585]
• 10: Daniel Gruhl , R. Guha , David Liben-Nowell , Andrew Tomkins, Information diffusion through blogspace, Proceedings of the 13th international conference on World Wide Web, May 17-20, 2004, New York, NY, USA [doi>10.1145/988672.988739]
• 11: Jason Hartline , Vahab Mirrokni , Mukund Sundararajan, Optimal marketing strategies over social networks, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China [doi>10.1145/1367497.1367524]
• 12: David Kempe , Jon Kleinberg , Éva Tardos, Maximizing the spread of influence through a social network, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2003, Washington, D.C. [doi>10.1145/956750.956769]
• 13: G. Kossinets, J. Kleinberg, and D. Watts. The Structure of Information Pathways in a Social Communication Network. In ACM SIGKDD, 2003.
• 14: K. Lerman and L. Jones. Social Browsing on Flickr. In Proc. of Int. Conf. on Weblogs and Social Media, 2007.
• 15: Jure Leskovec , Lada A. Adamic , Bernardo A. Huberman, The dynamics of viral marketing, ACM Transactions on the Web (TWEB), v.1 n.1, p.5-es, May 2007 [doi>10.1145/1232722.1232727]
• 16: Jure Leskovec , Eric Horvitz, Planetary-scale views on a large instant-messaging network, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China [doi>10.1145/1367497.1367620]
• 17: Jure Leskovec , Kevin J. Lang , Anirban Dasgupta , Michael W. Mahoney, Statistical properties of community structure in large social and information networks, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China [doi>10.1145/1367497.1367591]
• 18: D. Liben-Nowell and J. Kleinberg. Tracing Information Flow on a Global Scale using Internet Chain--Letter Data. Proc. Natl. Acad. Sci. USA, 2008.
• 19: R. M. May and A. L. Lloyd. Infection Dynamics on Scale-Free Networks. Physical Review E, 2001.
• 20: M. Mcpherson, L. Smith-Lovin, and J. M. Cook. Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology, 27:415--ì444, 2001.
• 21: Alan Mislove , Hema Swetha Koppula , Krishna P. Gummadi , Peter Druschel , Bobby Bhattacharjee, Growth of the flickr social network, Proceedings of the first workshop on Online social networks, August 18-18, 2008, Seattle, WA, USA [doi>10.1145/1397735.1397742]
• 22: Alan Mislove , Massimiliano Marcon , Krishna P. Gummadi , Peter Druschel , Bobby Bhattacharjee, Measurement and analysis of online social networks, Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, October 24-26, 2007, San Diego, California, USA [doi>10.1145/1298306.1298311]
• 23: R. Pastor-Satorras and A. Vespignani. Epidemics and Immunization in Scale-Free Networks. Wiley, Berlin, 2005.
• 24: Matthew Richardson , Pedro Domingos, Mining knowledge-sharing sites for viral marketing, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada [doi>10.1145/775047.775057]
• 25: E. M. Rogers. Diffusion of Innovations. Free Press, New York, 5th edition, 2003.
• 26: TechCrunch, 2 Billion Photos on Flickr.
• 27: T. W. Valente. Network Models of the Diffusion of Innovations. Hampton Press, Cresskill, N.J., 1995.
• 28: D. J. Watts. A Simple Model of Global Cascades on Random Networks. Proc. Natl. Acad. Sci. USA, 2002.
• 29: D. J. Watts, P. S. Dodds, and M. E. J. Newman. Identity and Search in Social Networks. Science, 294:1302--ì1305, 2002.
• 30: D. J. Watts and J. Peretti. Viral Marketing for the Real World. Harvard Business Review, 2007.
• 31: YouTube Fact Sheet.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services
          Subjects: Web-based services

Additional Classification:
  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES
      Subjects: Sociology

General Terms:
Human Factors, Measurement

Keywords:
cascades, flickr, information dissemination, social networks, viral marketing