Browse wiki

Jump to: navigation, search
On the evolution of Wikipedia
Abstract A recent phenomenon on the Web is the emerA recent phenomenon on the Web is the emergence and proliferation of new social media systems allowing social interaction between people. One of the most popular of these systems is Wikipedia that allows users to create content in a collaborative way. Despite its current popularity, not much is known about how users interact with Wikipedia and how it has evolved over time. In this paper we aim to provide a first, extensive study of the user behavior on Wikipedia and its evolution. Compared to prior studies, our work differs in several ways. First, previous studies on the analysis of the user workloads (for systems such as peer-to-peer systems [10] and Web servers [2]) have mainly focused on understanding the users who are accessing information. In contrast, Wikipedia’s provides us with the opportunity to understand how users create and maintain information since it provides the complete evolution history of its content. Second, the main focus of prior studies is evaluating the implication of the user workloads on the system performance, while our study is trying to understand the evolution of the data corpus and the user behavior themselves. Our main findings include that (1) the evolution and updates of Wikipedia is governed by a self-similar process, not by the Poisson process that has been observed for the general Web [4, 6] and (2) the exponential growth of Wikipedia is mainly driven by its rapidly increasing user base, indicating the importance of its open editorial policy for its current success. We also find that (3) the number of updates made to the Wikipedia articles exhibit a power-law distribution, but the distribution is less skewed than those obtained from other studies.ed than those obtained from other studies.
Added by wikilit team Added on initial load  +
Collected data time dimension Longitudinal  +
Conclusion Based on this characterization we were ablBased on this characterization we were able to find that Wikipedia evolution is a self-similar process growing exponentially mostly because of its increasing number of contributors. Moreover, we show that Wikipedia contributors are naturally split into distinct groups based on their behavior and that although the contributors have a broad range of interests in most of their visits they only focus on a single article. On the article side we were able to see that the number of changes to an article follows a power law that is less skewed than one would expect based on other workload studies.ld expect based on other workload studies.
Data source Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22On%2Bthe%2Bevolution%2Bof%2BWikipedia%22  +
Has author Rodrigo B. Almeida + , Barzan Mozafari + , Junghoo Cho +
Has domain Computer science +
Has topic Participation trends +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in International Conference on Weblogs and Social Media +
Research design Statistical analysis  +
Research questions This paper tries to model the behavior of users contributing to Wikipedia (hereafter called contributors) as a way of understanding its evolution over time. It presents what we believe to be the first extensive effort in that direction.
Revid 10,888  +
Theories Undetermined
Theory type Analysis  +
Title On the evolution of Wikipedia
Unit of analysis Article  + , Edit  + , User  +
Url http://www.icwsm.org/papers/2--Almeida-Mozafari-Cho.pdf  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Dump  +
Wikipedia language English  +
Wikipedia page type Article  +
Year 2007  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:29:46  +
Categories Participation trends  + , Computer science  + , Publications with missing comments  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:30:11  +
hide properties that link here 
  No properties link to this page.
 

 

Enter the name of the page to start browsing from.