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A Simple Generative Model of Collective Online Behaviour | | James P. Gleeson
; Davide Cellai
; Jukka-Pekka Onnela
; Mason A. Porter
; Felix Reed-Tsochas
; | | Date: |
31 May 2013 | | Abstract: | Human activities---from voter mobilization to political
protests---increasingly take place in online environments, providing novel
opportunities for relating individual behaviours to population-level outcomes.
The recent availability of data sets that capture the behaviour of individuals
participating in online social systems has driven the emerging field of
computational social science, as large-scale empirical data sets enable the
development of detailed computational models of individual and collective
behaviour. Given the inherent limitations of observational data, it is crucial
to investigate the extent to which models of collective dynamics can
distinguish between different individual-level mechanisms. Here we introduce a
simple generative model for the collective behaviour of millions of social
networking site users who are deciding between different software applications.
Our model incorporates two distinct components: 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 behaviour that is consistent with data, only models that
strongly emphasize recent popularity of applications over their cumulative
popularity reproduce the observed temporal dynamics. Our approach demonstrates
the value of even very simple generative models in understanding collective
social behaviour, and it highlights the need to address temporal dynamics---not
just long-time behaviour---when modelling complex social systems. | | Source: | arXiv, 1305.7440 | | Services: | Forum | Review | PDF | Favorites | |
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