Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Foundations and Trends in Web Science
Power-Law Distributions in Empirical Data
SIAM Review
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
Networks: An Introduction
Web dynamics as a random walk: how and why power laws occur
Proceedings of the 3rd Annual ACM Web Science Conference
Scalable analysis for large social networks: the data-aware mean-field approach
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
Preferential attachment in online networks: measurement and explanations
Proceedings of the 5th Annual ACM Web Science Conference
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It is generally thought that the World Wide Web belongs to the class of complex networks that is scale-free: the distribution of the number of links that nodes have follows a power law ('rich-get-richer' effect). This phenomenon is explained by a combination of theoretical-computational and empirical analysis based on stochastic network models. However, current network models embody a number of assumptions and idealizations that are not valid for the Web. Better and richer network models are needed, in association with a much more refined and in-depth empirical data gathering and analysis. In particular, the understanding of the dynamics leaves much to desire. In this paper we present a dynamic network model that avoids a number of unrealistic idealizations commonly introduced. We show how properties such as average degree and power laws are the outcome of dynamic network parameters. Exemplified by a Wikipedia case study, we show how these dynamic parameters might be empirically measured directly. We falsify several widely held ideas about the emergence of power laws: (i) that they are related to growing networks; (ii) that they are related to (linear) preferential attachment; (iii) that they may hold strictly. Power laws do not have the status of a first principle in networks: if they hold, they are just conditional and approximate empirical regularities.