On skewed distributions and straight lines: A case study on the wiki collaboration network

Osnat Mokryn, Alexey Reznik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we present a hypothesis that power laws are found only in datasets sampled from a static data, in which each and every item has gained its maximal importance and is not in the process of changing it during the sampling period. We motivate our hypothesis by examining languages, and word-ranking distribution as it appears in books, and in the Bible. To demonstrate the validity of our hypothesis, we experiment with the Wikipedia edit collaboration network. We find that the dataset fits a skewed distribution. Next, we identify its dynamic part. We then show that when the modified part is removed from the obtained dataset, the remaining static part exhibits a good fit to a power law distribution.

Original languageEnglish
Title of host publicationWWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages1089-1094
Number of pages6
ISBN (Electronic)9781450334730
DOIs
StatePublished - 18 May 2015
Externally publishedYes
Event24th International Conference on World Wide Web, WWW 2015 - Florence, Italy
Duration: 18 May 201522 May 2015

Publication series

NameWWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web

Conference

Conference24th International Conference on World Wide Web, WWW 2015
Country/TerritoryItaly
CityFlorence
Period18/05/1522/05/15

Keywords

  • Collaboration networks
  • Dynamic distributions
  • Power law distribution
  • Skewed distributions
  • Trends
  • Wikipedia

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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