research-article

Predicting emerging social conventions in online social networks

Authors:

Winter A. Mason,

Krishna P. Gummadi,

Meeyoung ChaAuthors Info & Claims

CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

Pages 445 - 454

https://doi.org/10.1145/2396761.2396820

Published: 29 October 2012 Publication History

Abstract

The way in which social conventions emerge in communities has been of interest to social scientists for decades. Here we report on the emergence of a particular social convention on Twitter---the way to indicate a tweet is being reposted and attributing the content to its source. Despite being invented at different times and having different adoption rates, only two variations became widely adopted. In this paper we describe this process in detail, highlighting the factors that come into play in deciding which variation individuals will adopt. Our classification analysis demonstrates that the date of adoption and the number of exposures are particularly important in the adoption process, while personal features (such as the number of followers and join date) and the number of adopter friends have less discriminative power in predicting adoptions. We discuss implications of these findings in the design of future Web applications and services.

References

[1]

I. Ajzen and M. Fishbein. The prediction of behavior from attitudinal and normative variables. Journal of Experimental Social Psychology, 6:466--487, 1970.

[2]

S. E. Asch. Opinions and Social Pressure. Scientific American, 193:31--35, 1955.

[3]

R. Axelrod. An Evolutionary Approach to Norms. American Political Science Review, 1986.

[4]

E. Bakshy, I. Rosenn, C. Marlow, and L. Adamic. The Role of Social Networks in Information Diffusion. In proc. of the International World Wide Web Conference, 2012.

Digital Library

[5]

F. Barth. Process and Form in Social Life. Routledge & Kegan Paul, 1981.

[6]

R. Baumeister and M. Leary. The Need to Belong: Desire for Interpersonal Attachments as a Fundamental Human Motivation. Psychological Bulletin, 1995.

[7]

B. Becker and G. Mark. Social conventions in collaborative virtual environments. In proc. of the International Conference on Collaborative Virtual Environments, 1998.

[8]

D. M. R. Bernardo A. Huberman and F. Wu. Social networks that matter: Twitter under the microscope. First Monday, 14(1), Jan. 2009.

[9]

Bibb Latané and S. Wolf. The social impact of majorities and minorities. Psychological Review, 88:438--453, 1981.

[10]

d. boyd, S. Golder, and G. Lotan. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. In proc. of the Hawaii International Conference on System Sciences, 2010.

Digital Library

[11]

R. Boyd and P. J. Richerson. Why does culture increase human adaptability? Ethology and Sociobiology, 16:125--143, 1995.

[12]

B. P. Buunk and A. B. Bakker. Extradyadic sex: The role of descriptive and injunctive norms. Journal of Sex Research, 32(4):313--318, Jan. 1995.

[13]

D. Centola. The Spread of Behavior in an Online Social Network Experiment. Science, 329(5996):1194--1197, Sept. 2010.

[14]

M. Cha, H. Haddadi, F. Benevenuto, and K. Gummadi. Measuring User Influence in Twitter: The Million Follower Fallacy. In proc. of the International AAAI Conference on Weblogs and Social Media, 2010.

[15]

N. Christakis and J. H. Fowler. The Spread of Obesity in a Large Social Network over 32 Years. New England Journal of Medicine, 2007.

[16]

R. B. Cialdini. Influence: Science and practice. HarperCollins, 3 edition, 1993.

[17]

R. B. Cialdini and M. R. Trost. Social Influence: Social norms, conformity, and compliance. In D. T. Gilbert, S. T. Fiske, and L. Gardner, editors, The Handbook of Social Psychology, pages 151--192. McGraw-Hill, New York, 1998.

[18]

E. Cohen-Cole and J. M. Fletcher. Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic. Journal of Health Economics, 27:1382--1387, 2008.

[19]

J. Delgado. Emergence of social conventions in complex networks. Artificial Intelligence, 141(1-2):171--185, 2002.{

Digital Library

[20]

M. Deutsch and H. B. Gerard. A study of normative and informative social influences upon individual judgment. Journal of Abnormal Psychology, 51:629--636, 1955.

[21]

D. C. Feldman. The development and enforcement of group norms. The Academy of Management Review, 9(1):47--53, 1984.

[22]

L. Festinger. A theory of social comparison processes. Human Relations, 7(2):117--140, 1954.

[23]

J. H. Fowler and N. A. Christakis. Cooperative behavior cascades in human social networks. Proceedings of the National Academy of Sciences, 107(12):5334--5338, Mar. 2010.

[24]

N. E. Friedkin. Norm Formation in Social Influence Networks. Social Networks, 23:167--189, 2001.

[25]

H. B. Gerard. The Anchorage of Opinions in Face-to-Face Groups. Human Relations, 7(3):313--325, Aug. 1954.

[26]

H. B. Gerard, R. A. Wilhelmy, and E. S. Conolley. Conformity and group size. Journal of Personality and Social Psychology, 8:79--82, 1968.

[27]

S. Goyal and M. C. W. Janssen. Non-Exclusive Conventions and Social Coordination. Journal of Economic Theory, 77(1):34--57, 1997.

[28]

C. A. Insko, R. H. Smith, M. D. Alicke, J. Wade, and S. Taylor. Conformity and group size: The concern with being right and the concern with being liked. Personality and Social Psychology Bulletin, 11:41--50, 1985.

[29]

F. Kooti, H. Yang, M. Cha, K. Gummadi, and W. A. Mason. The emergence of conventions in online social networks. In proc. of the International AAAI Conference on Weblogs and Social Media, 2012.

[30]

J. Levine and R. L. Moreland. Progress in Small Group Research. Annual Reviews in Psychology, 41:585--634, 1990.

[31]

S. Milgram, L. Bickman, and L. Berkowitz. Note on the drawing power of crowds of different size. Journal of Personality and Social Psychology, 13(2):79--82, 1969.

[32]

T. M. Newcomb. Personality and social change. Dryden, 1943.

[33]

K.-D. Opp. How do norms emerge? An outline of a theory. Mind & Society, 3(2):101--128, 2001.

[34]

E. Ostrom. Collective Action and the Evolution of Social Norms. The Journal of Economic Perspectives, 14:137--158, 2000.

[35]

M. Pennacchiotti and A.-M. Popescu. Democrats, Republicans and Starbucks Afficionados: User Classification in Twitter. In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2011.

Digital Library

[36]

A. Riley and P. J. Burke. Identities and Self-Verification in the Small Group. Social Psychology Quarterly, 58(2):61--73, 1995.

[37]

E. M. Rogers. Diffusion of Innovations. Free Press, 1983.

[38]

D. M. Romero, B. Meeder, and J. Kleinberg. Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contagion on Twitter. In proc. of the International World Wide Web Conference, 2011.

Digital Library

[39]

M. Salganik, P. S. Dodds, and D. J. Watts. Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science, 311:854--856, 2006.

[40]

B. Savarimuthu, S. Cranefield, and M. Purvis. Role Model Based Mechanism for Norm Emergence in Artificial Agent Societies. In proc. of the AAMAS'07 Workshop on Coordination, Organization, Institutions and Norms in Agent Systems, 2007.

Digital Library

[41]

M. Sherif. The psychology of social norms. Harper, 1936.

[42]

Y. Shoham and M. Tennenholtz. On the emergence of social conventions: modeling, analysis, and simulations. Artificial Intelligence, 94(1-2):139--166, 1997.

Digital Library

[43]

D. M. Taylor and W. Louis. Terrorism and the quest for identity. In F. M. Moghaddam and A. J. Marsella, editors, Understanding terrorism: Psychosocial roots, consequences, and interventions, volume 343, pages 169--185. American Psychological Association, 2004.

[44]

A. Walker and M. Wooldridge. Understanding the emergence of conventions in multi-agent systems. In proc. of the International Conference on Multi-Agent Systems, 1995.

[45]

WEKA website. http://www.cs.waikato.ac.nz/ml/weka.

[46]

D. Wilkes-Gibbs and H. Clark. Coordinating beliefs in conversation. Journal of Memory and Language, 31(2):183--194, 1992.

[47]

M. P. Zanna and J. M. Olson. Individual differences in attitudinal relations. In M. P. Zanna, E. T. Higgins, and C. P. Herman, editors, Consistency in social behavior: The Ontario Symposium, volume 2, pages 75--103. Erlbaum, 1982.

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https://doi.org/10.1016/j.socnet.2022.12.006
Gligoric KCzestochowska JAnderson AWest R(2022)Anticipated versus Actual Effects of Platform Design Change: A Case Study of Twitter's Character LimitProceedings of the ACM on Human-Computer Interaction10.1145/35556596:CSCW2(1-29)Online publication date: 11-Nov-2022
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Iacopini IPetri GBaronchelli ABarrat A(2022)Group interactions modulate critical mass dynamics in social conventionCommunications Physics10.1038/s42005-022-00845-y5:1Online publication date: 18-Mar-2022
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Index Terms

Predicting emerging social conventions in online social networks
1. Applied computing
  1. Law, social and behavioral sciences
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

October 2012

2840 pages

ISBN:9781450311564

DOI:10.1145/2396761

General Chair:
Xuewen Chen
Wayne State University, USA
,
Program Chairs:
Guy Lebanon
Georgia Institute of Technology
,
Haixun Wang
Microsoft Research Asia
,
Mohammed J. Zaki
Rensselaer Polytechnic Institute

Copyright © 2012 ACM.

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Published: 29 October 2012

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https://doi.org/10.1016/j.socnet.2022.12.006
Gligoric KCzestochowska JAnderson AWest R(2022)Anticipated versus Actual Effects of Platform Design Change: A Case Study of Twitter's Character LimitProceedings of the ACM on Human-Computer Interaction10.1145/35556596:CSCW2(1-29)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555659
Iacopini IPetri GBaronchelli ABarrat A(2022)Group interactions modulate critical mass dynamics in social conventionCommunications Physics10.1038/s42005-022-00845-y5:1Online publication date: 18-Mar-2022
https://doi.org/10.1038/s42005-022-00845-y
Tu ZCao HLagerspetz EFan YFlores HTarkoma SNurmi PLi Y(2021)Demographics of mobile app usage: long-term analysis of mobile app usageCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-020-00041-33:3(235-252)Online publication date: 21-Apr-2021
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Zia KFarooq UAl-Maskari SShafi M(2021)Co-evolution of Knowledge Diffusion and Absorption: A Simulation-Based AnalysisComputational Science – ICCS 202110.1007/978-3-030-77961-0_46(570-584)Online publication date: 9-Jun-2021
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Hasan MRaja ABazzan A(2019)A context-aware convention formation framework for large-scale networksAutonomous Agents and Multi-Agent Systems10.1007/s10458-018-9397-933:1-2(1-34)Online publication date: 1-Mar-2019
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Centola DBecker JBrackbill DBaronchelli A(2018)Experimental evidence for tipping points in social conventionScience10.1126/science.aas8827360:6393(1116-1119)Online publication date: 8-Jun-2018
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