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What is Twitter, a social network or a news media?

Published:26 April 2010Publication History

ABSTRACT

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing.

We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks [28]. In order to identify influentials on Twitter, we have ranked users by the number of followers and by PageRank and found two rankings to be similar. Ranking by retweets differs from the previous two rankings, indicating a gap in influence inferred from the number of followers and that from the popularity of one's tweets. We have analyzed the tweets of top trending topics and reported on their temporal behavior and user participation. We have classified the trending topics based on the active period and the tweets and show that the majority (over 85%) of topics are headline news or persistent news in nature. A closer look at retweets reveals that any retweeted tweet is to reach an average of 1,000 users no matter what the number of followers is of the original tweet. Once retweeted, a tweet gets retweeted almost instantly on next hops, signifying fast diffusion of information after the 1st retweet.

To the best of our knowledge this work is the first quantitative study on the entire Twittersphere and information diffusion on it.

References

  1. Y.-Y. Ahn, S. Han, H. Kwak, S. Moon, and H. Jeong. Analysis of topological characteristics of huge online social networking services. In Proc. of the 16th international conference on World Wide Web. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. E. Almaas, B. Kovács, T. Vicsek, Z. N. Oltvai, and A. L. Barabási. Global organization of metabolic fluxes in the bacterium escherichia coli. Nature, 427(6977):839--843, February 2004.Google ScholarGoogle ScholarCross RefCross Ref
  3. F. Benevenut, T. Rodrigues, M. Cha, and V. Almeida. Characterizing user behavior in online social networks. In Proc. of ACM SIGCOMM Internet Measurement Conference. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. Cha, A. Mislove, and K. P. Gummadi. A measurement-driven analysis of information propagation in the Flickr social network. In Proc. of the 18th international conference on World Wide Web. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. H. Chun, H. Kwak, Y.-H. Eom, Y.-Y. Ahn, S. Moon, and H. Jeong. Comparison of online social relations in volume vs interaction: a case study of Cyworld. In Proc. of the 8th ACM SIGCOMM Internet Measurement Conference. ACM, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Clean Tweets. http://blvdstatus.com/clean-tweets.html.Google ScholarGoogle Scholar
  7. R. Crane and D. Sornette. Robust dynamic classes revealed by measuring the response function of a social system. Proc. of the National Academy of Sciences, 105(41):15649--15653, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  8. R. Fagin, R. Kumar, and D. Sivakumar. Comparing top k lists. In Proc. of the 14th annual ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Flu Trends. http://www.google.org/flutrends/.Google ScholarGoogle Scholar
  10. D. Gruhl, R. Guha, D. Liben-Nowell, and A. Tomkins. Information diffusion through blogspace. In Proc. of the 13th international conference on World Wide Web. ACM, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. B. A. Huberman, D. M. Romero, and F. Wu. Social networks that matter: Twitter under the microscope. arXiv:0812.1045v1, Dec 2008.Google ScholarGoogle Scholar
  12. HubSpot. State of the twittersphere. http://bit.ly/sotwitter, June 2009.Google ScholarGoogle Scholar
  13. B. J. Jansen, M. Zhang, K. Sobel, and A. Chowdury. Micro-blogging as online word of mouth branding. In Proc. of the 27th international conference extended abstracts on Human factors in computing systems. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. A. Java, X. Song, T. Finin, and B. Tseng. Why we twitter: understanding microblogging usage and communities. In Proc. of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network. In Proc. of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. M. Kendall. A new measure of rank correlation. Biometrika, 30(1-2):81--93, 1938.Google ScholarGoogle ScholarCross RefCross Ref
  17. B. Krishnamurthy, P. Gill, and M. Arlitt. A few chirps about twitter. In Proc. of the 1st workshop on Online social networks. ACM, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. R. Kumar, J. Novak, and A. Tomkins. Structure and evolution of online social networks. In Proc. of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. J. Leskovec, L. A. Adamic, and B. A. Huberman. The dynamics of viral marketing. In Proc. of the 7th ACM conference on Electronic commerce. ACM, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. J. Leskovec, L. Backstrom, and J. Kleinberg. Meme-tracking and the dynamics of the news cycle. In Proc. of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. J. Leskovec and E. Horvitz. Worldwide buzz: Planetary-scale views on an instant-messaging network. Technical report, Microsoft Research, June 2007.Google ScholarGoogle Scholar
  22. J. Leskovec and E. Horvitz. Planetary-scale views on a large instant-messaging network. In Proc. of the 17th international conference on World Wide Web. ACM, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. J. Leskovec, J. Kleinberg, and C. Faloutsos. Graphs over time: densification laws, shrinking diameters and possible explanations. In Proc. of the 11th ACM SIGKDD international conference on Knowledge discovery in data mining. ACM, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. D. Liben-Nowell and J. Kleinberg. Tracing information flow on a global scale using Internet chain-letter data. Proc. of the National Academy of Sciences, 105(12):4633--4638, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  25. F. McCown and M. L. Nelson. Agreeing to disagree: search engines and their public interfaces. In Proc. of the 7th ACM/IEEE-CS joint conference on Digital libraries. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. M. McPherson, L. Smith-Lovin, and J. M. Cook. Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27(1):415--444, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  27. S. Milgram. The small world problem. Psychology today, 2(1):60--67, 1967.Google ScholarGoogle Scholar
  28. M. E. J. Newman and J. Park. Why social networks are different from other types of networks. Phys. Rev. E, 68(3):036122, Sep 2003.Google ScholarGoogle ScholarCross RefCross Ref
  29. L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab, November 1999.Google ScholarGoogle Scholar
  30. R. Pastor-Satorras and A. Vespignani. Epidemics and immunization in scale-free networks. arXiv:cond-mat/0205260v1, May 2002.Google ScholarGoogle Scholar
  31. E. Reinikainen. #iranelectioncyberwarguideforbeginners. http://goo.gl/pZvi, June 2009.Google ScholarGoogle Scholar
  32. E. M. Rogers. Diffusion of Innovations. Free Press, 5 edition, August 2003.Google ScholarGoogle Scholar
  33. D. Strang and S. Soule. Diffusion in organizations and social movements: From hybrid corn to poison pills. Annual Review of Sociology, 24:265--290, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  34. E. Sun, I. Rosenn, C. Marlow, and T. Lento. Gesundheit! modeling contagion through facebook news feed. In Proc. of International AAAI Conference on Weblogs and Social Media, 2009.Google ScholarGoogle Scholar
  35. The New York Times. http://bits.blogs.nytimes.com/2009/07/07/spammers-shorten-their-urls/.Google ScholarGoogle Scholar
  36. Twitter Search API. http://apiwiki.twitter.com/Twitter-API-Documentation.Google ScholarGoogle Scholar
  37. D. J. Watts and S. H. Strogatz. Collective dynamics of small-world networks. Nature, 393:440--442, Jun 1998.Google ScholarGoogle ScholarCross RefCross Ref
  38. J. Weng, E.-P. Lim, J. Jiang, and Q. He. Twitterrank: finding topic-sensitive influential twitterers. In Proc. of the third ACM international conference on Web search and data mining. ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. C. Wilson, B. Boe, A. Sala, K. P. Puttaswamy, and B. Y. Zhao. User interactions in social networks and their implications. In Proc. of the 4th ACM European conference on Computer systems. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. D. Zhao and M. B. Rosson. How and why people twitter: the role that micro-blogging plays in informal communication at work. In Proceedings of the ACM 2009 international conference on Supporting group work. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

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