Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1772690.1772751acmotherconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
research-article

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

Published: 26 April 2010 Publication 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.
[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.
[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.
[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.
[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.
[6]
Clean Tweets. http://blvdstatus.com/clean-tweets.html.
[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.
[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.
[9]
Flu Trends. http://www.google.org/flutrends/.
[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.
[11]
B. A. Huberman, D. M. Romero, and F. Wu. Social networks that matter: Twitter under the microscope. arXiv:0812.1045v1, Dec 2008.
[12]
HubSpot. State of the twittersphere. http://bit.ly/sotwitter, June 2009.
[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.
[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.
[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.
[16]
M. Kendall. A new measure of rank correlation. Biometrika, 30(1-2):81--93, 1938.
[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.
[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.
[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.
[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.
[21]
J. Leskovec and E. Horvitz. Worldwide buzz: Planetary-scale views on an instant-messaging network. Technical report, Microsoft Research, June 2007.
[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.
[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.
[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.
[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.
[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.
[27]
S. Milgram. The small world problem. Psychology today, 2(1):60--67, 1967.
[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.
[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.
[30]
R. Pastor-Satorras and A. Vespignani. Epidemics and immunization in scale-free networks. arXiv:cond-mat/0205260v1, May 2002.
[31]
E. Reinikainen. #iranelectioncyberwarguideforbeginners. http://goo.gl/pZvi, June 2009.
[32]
E. M. Rogers. Diffusion of Innovations. Free Press, 5 edition, August 2003.
[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.
[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.
[35]
The New York Times. http://bits.blogs.nytimes.com/2009/07/07/spammers-shorten-their-urls/.
[36]
Twitter Search API. http://apiwiki.twitter.com/Twitter-API-Documentation.
[37]
D. J. Watts and S. H. Strogatz. Collective dynamics of small-world networks. Nature, 393:440--442, Jun 1998.
[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.
[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.
[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.

Cited By

View all
  • (2024)Manifestation discursive des combats de féministes africaines Nouvelles voix/voies des discours politiques en Afrique francophone10.4000/books.pufc.53391Online publication date: 26-Jan-2024
  • (2024)Analysis of Rumor Propagation Model Based on Coupling Interaction Between Official Government and Media WebsitesSystems10.3390/systems1211045112:11(451)Online publication date: 25-Oct-2024
  • (2024)Shifting Workplace Paradigms: Twitter Sentiment Insights on Work from HomeSustainability10.3390/su1602087116:2(871)Online publication date: 19-Jan-2024
  • Show More Cited By

Index Terms

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

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    WWW '10: Proceedings of the 19th international conference on World wide web
    April 2010
    1407 pages
    ISBN:9781605587998
    DOI:10.1145/1772690

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 April 2010

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Twitter
    2. degree of separation
    3. homophily
    4. influential
    5. information diffusion
    6. online social network
    7. pagerank
    8. reciprocity
    9. retweet

    Qualifiers

    • Research-article

    Conference

    WWW '10
    WWW '10: The 19th International World Wide Web Conference
    April 26 - 30, 2010
    North Carolina, Raleigh, USA

    Acceptance Rates

    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)1,436
    • Downloads (Last 6 weeks)172
    Reflects downloads up to 12 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Manifestation discursive des combats de féministes africaines Nouvelles voix/voies des discours politiques en Afrique francophone10.4000/books.pufc.53391Online publication date: 26-Jan-2024
    • (2024)Analysis of Rumor Propagation Model Based on Coupling Interaction Between Official Government and Media WebsitesSystems10.3390/systems1211045112:11(451)Online publication date: 25-Oct-2024
    • (2024)Shifting Workplace Paradigms: Twitter Sentiment Insights on Work from HomeSustainability10.3390/su1602087116:2(871)Online publication date: 19-Jan-2024
    • (2024)Profiling Social Sentiment in Times of Health Emergencies with Information from Social Networks and Official StatisticsMathematics10.3390/math1206091112:6(911)Online publication date: 20-Mar-2024
    • (2024)Identification of Domain-specific Opinion Leaders in X/TwitterX/Twitter'da Alana Özgü Kanaat Önderlerinin Belirlenmesiİçtimaiyat10.33709/ictimaiyat.1404626Online publication date: 29-Jan-2024
    • (2024)AN IN-DEPTH EXPLORATION INTO RELATIONSHIP OF SOCIAL MEDIA USAGE AND PSYCHOLOGICAL WELL-BEING: AN INSIGHTFUL PERSPECTIVE OF NETWORKING SOCIETYShodhKosh: Journal of Visual and Performing Arts10.29121/shodhkosh.v5.i2.2024.8965:2Online publication date: 29-Feb-2024
    • (2024)A Survey on Event Tracking in Social Media Data StreamsBig Data Mining and Analytics10.26599/BDMA.2023.90200217:1(217-243)Online publication date: Mar-2024
    • (2024)The impact of information technology governance according to the COBIT on performanceInternational Journal of ADVANCED AND APPLIED SCIENCES10.21833/ijaas.2024.03.01411:3(127-136)Online publication date: Mar-2024
    • (2024)Dual Communication in a Social Network: Contributing and Dedicating AttentionSSRN Electronic Journal10.2139/ssrn.4758215Online publication date: 2024
    • (2024)Prediction Analysis on Trending Twitter Hashtags Using Machine LearningSSRN Electronic Journal10.2139/ssrn.4487088Online publication date: 2024
    • Show More Cited By

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    ePub

    View this article in ePub.

    ePub

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media