Taming a menagerie of heavy tails with skew path analysis

Josh Introne, Sean Goggins

Research output: Chapter in Book/Entry/PoemConference contribution

2 Scopus citations


The discovery of stable, heavy-tailed distributions of activity on the web has inspired many researchers to search for simple mechanisms that can cut through the complexity of countless social interactions to yield powerful new theories about human behavior. A dominant mode of investigation involves fitting a mathematical model to an observed distribution, and then inferring the behaviors that generate the modeled distribution. Yet, distributions of activity are not always stable, and the process of fitting a mathematical model to empirical distributions can be highly uncertain, especially for smaller and highly variable datasets. In this paper, we introduce an approach called skew-path analysis, which measures how concentrated information production is along different dimensions in community-generated data. The approach scales from small to large datasets, and is suitable for investigating the dynamics of online behavior. We offer a preliminary demonstration of the approach by using it to analyze six years of data from an online health community, and show that the technique offers interesting insights into the dynamics of information production. In particular, we find evidence for two distinct point attractors within a subset of the forums analyzed, demonstrating the utility of the approach.

Original languageEnglish (US)
Title of host publicationProceedings of the 2015 ACM Web Science Conference
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450336727
StatePublished - Jun 28 2015
Externally publishedYes
Event7th ACM Web Science Conference, WebSci 2015 - Oxford, United Kingdom
Duration: Jun 28 2015Jul 1 2015

Publication series

NameProceedings of the 2015 ACM Web Science Conference


Conference7th ACM Web Science Conference, WebSci 2015
Country/TerritoryUnited Kingdom


  • Diversity
  • Dynamics
  • Power Law
  • Social media

ASJC Scopus subject areas

  • Computer Networks and Communications


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