Modeling Website Popularity Competition in the Attention-Activity Marketplace

How does a new startup drive the popularity of competing websites into oblivion like Facebook famously did to MySpace? This question is of great interest to academics, technologists, and financial investors alike. In this work we exploit the singular way in which Facebook wiped out the popularity of MySpace, Hi5, Friendster, and Multiply to guide the design of a new popularity competition model. Our model provides new insights into what Nobel Laure- ate Herbert A. Simon called the "marketplace of attention," which we recast as the attention-activity marketplace. Our model design is further substantiated by user-level activity of 250,000 MySpace users obtained between 2004 and 2009. The resulting model not only accurately fits the observed Daily Active Users (DAU) of Facebook and its competitors but also predicts their fate four years into the future.

[1]  Bruno Ribeiro,et al.  Modeling and predicting the growth and death of membership-based websites , 2013, WWW.

[2]  Germany,et al.  Wilson renormalization of a reaction–diffusion process , 1997, cond-mat/9706197.

[3]  W. Ebeling.  Stochastic Processes in Physics and Chemistry , 1995 .

[4]  J. C. Fisher,et al.  A simple substitution model of technological change , 1971 .

[5]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[6]  Ravi Kumar,et al.  Structure and evolution of online social networks , 2006, KDD '06.

[7]  Don Towsley,et al.  On MySpace Account Spans and Double Pareto-Like Distribution of Friends , 2010, 2010 INFOCOM IEEE Conference on Computer Communications Workshops.

[8]  N. Christakis,et al.  The Spread of Obesity in a Large Social Network Over 32 Years , 2007, The New England journal of medicine.

[9]  Frank M. Bass,et al.  Comments on "A New Product Growth for Model Consumer Durables The Bass Model" , 2004, Manag. Sci..

[10]  C. Shapiro,et al.  Network Externalities, Competition, and Compatibility , 1985 .

[11]  E. Rogers,et al.  Diffusion of Innovations , 1964 .

[12]  Andrea Montanari,et al.  The spread of innovations in social networks , 2010, Proceedings of the National Academy of Sciences.

[13]  Gabrielle Demange,et al.  A Survey of Network Formation Models: Stability and Efficiency , 2005 .

[14]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[15]  M Girvan,et al.  Structure of growing social networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Sree Hari Krishnan Parthasarathi,et al.  Exploiting innocuous activity for correlating users across sites , 2013, WWW.

[17]  Christos Faloutsos,et al.  Interacting viruses in networks: can both survive? , 2012, KDD.

[18]  Jure Leskovec,et al.  Microscopic evolution of social networks , 2008, KDD.

[19]  Lars Backstrom,et al.  Structural diversity in social contagion , 2012, Proceedings of the National Academy of Sciences.

[20]  References , 1971 .

[21]  Sanjeev Goyal,et al.  A Noncooperative Model of Network Formation , 2000 .

[22]  Christos Faloutsos,et al.  Winner takes all: competing viruses or ideas on fair-play networks , 2012, WWW.

[23]  Damon Centola,et al.  The Spread of Behavior in an Online Social Network Experiment , 2010, Science.

[24]  Jon M. Kleinberg,et al.  Center of Attention: How Facebook Users Allocate Attention across Friends , 2011, ICWSM.

[25]  P. Klemperer,et al.  Coordination and Lock-In: Competition with Switching Costs and Network Effects , 2006 .

[26]  Chen-Nee Chuah,et al.  Modeling/predicting the evolution trend of osn-based applications , 2013, WWW '13.

[27]  Stephen E. Margolis,et al.  Network externality : an uncommon tragedy , 1994 .

[28]  Krishna P. Gummadi,et al.  On the evolution of user interaction in Facebook , 2009, WOSN '09.

[29]  Jure Leskovec,et al.  The life and death of online groups: predicting group growth and longevity , 2012, WSDM '12.

[30]  N. Rashevsky,et al.  Mathematical biology , 1961, Connecticut medicine.

[31]  N. Kampen,et al.  Stochastic processes in physics and chemistry , 1981 .

[32]  Jon M. Kleinberg,et al.  Group formation in large social networks: membership, growth, and evolution , 2006, KDD '06.

[33]  T. Snijders.  Stochastic actor-oriented models for network change , 1996 .

[34]  J. C. Fisher,et al.  A Simple Substitution Model of Technological Change : Technological Forecasting and Social Change , 1988 .

[35]  Didier Sornette,et al.  Quis Pendit Ipsa Pretia: Facebook Valuation and Diagnostic of a Bubble Based on Nonlinear Demographic Dynamics , 2011 .

[36]  P. Geroski.  Models of technology diffusion , 2000 .

[37]  H. Peyton Young,et al.  The dynamics of social innovation , 2011, Proceedings of the National Academy of Sciences.

[38]  Mark S. Granovetter.  Threshold Models of Collective Behavior , 1978, American Journal of Sociology.

[39]  P. Klemperer,et al.  Chapter 31 Coordination and Lock-In: Competition with Switching Costs and Network Effects , 2007 .

[40]  Matteo Marsili,et al.  The rise and fall of a networked society: a formal model. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Alessandro Vespignani,et al.  Reaction–diffusion processes and metapopulation models in heterogeneous networks , 2007, cond-mat/0703129.

[42]  Alessandro Vespignani,et al.  Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations. , 2007, Journal of theoretical biology.

[43]  Christos Faloutsos,et al.  Graph evolution: Densification and shrinking diameters , 2006, TKDD.

[44]  T. Schelling.  Micromotives and Macrobehavior , 1978 .

[45]  B Skyrms,et al.  A dynamic model of social network formation. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[46]  W. Arthur,et al.  Increasing Returns and Path Dependence in the Economy , 1996 .

[47]  Pavlin Mavrodiev,et al.  Social resilience in online communities: the autopsy of friendster , 2013, COSN '13.