Download this Paper Open PDF in Browser

A Simple Generative Model of Collective Online Behaviour

Proceedings of the National Academy of Sciences of the USA, vol. 111 no. 29, 10411-10415.

36 Pages Posted: 19 Jun 2013 Last revised: 23 Jul 2014

James P. Gleeson

University of Limerick, Ireland

Davide Cellai

University of Limerick - Department of Mathematics and Statistics

Jukka-Pekka Onnela

Harvard University

Mason Alexander Porter

University of Oxford

Felix Reed-Tsochas

University of Oxford - Said Business School; University of Oxford - CABDyN Complexity Centre; Oxford Martin School; University of Oxford - Department of Sociology

Date Written: May 28, 2014

Abstract

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates — even when using purely observational data without experimental design — that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.

Keywords: modelling, collective behaviour, online social networks, branching processes, complex systems

Suggested Citation

Gleeson, James P. and Cellai, Davide and Onnela, Jukka-Pekka and Porter, Mason Alexander and Reed-Tsochas, Felix, A Simple Generative Model of Collective Online Behaviour (May 28, 2014). Proceedings of the National Academy of Sciences of the USA, vol. 111 no. 29, 10411-10415. . Available at SSRN: https://ssrn.com/abstract=2281114 or http://dx.doi.org/10.2139/ssrn.2281114

James Gleeson

University of Limerick, Ireland ( email )

MACSI
Dept of Mathematics and Statistics
Limerick
Ireland

HOME PAGE: http://www.ul.ie/gleesonj

Davide Cellai

University of Limerick - Department of Mathematics and Statistics ( email )

Limerick
Ireland

Jukka-Pekka Onnela

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Mason Porter (Contact Author)

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

Felix Reed-Tsochas

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

HOME PAGE: http://www.sbs.ox.ac.uk/community/people/felix-reed-tsochas

University of Oxford - CABDyN Complexity Centre ( email )

Park End Street
Oxford, OX1 1HP
United Kingdom

HOME PAGE: http://www.cabdyn.ox.ac.uk/people_pages/complexity_people_reedtsochas.asp

Oxford Martin School ( email )

University of Oxford
34 Broad Street
Oxford, OX1 3BD
United Kingdom

HOME PAGE: http://www.oxfordmartin.ox.ac.uk/people/14

University of Oxford - Department of Sociology ( email )

Manor Road
Manor Road
Oxford, OX1 3UQ
United Kingdom

HOME PAGE: http://www.sociology.ox.ac.uk/academic-staff/felix-reed-tsochas.html

Paper statistics

Downloads
26
Abstract Views
355