User-generated content (UGC) is becoming the most popular and valuable information available on the WWW. However, little serious research has been conducted to measure the properties of its production process. This paper presents an in-depth quantitative analysis of 9 popular websites that are based on different UGC types. The Information Production Process is used as a framework for the analysis. The findings provide for first time strong scientific evidence for previously anecdotic knowledge: UGC production follows “long-tail” distributions and it is marked with a strong “participation inequality”. Also, the analysis arrived to unexpected findings: not all the UGC types follow the inverse power-law distribution, and large content collections could be dominated by the presence of ultraproductive users. The analysis results also have implications for the administration of UGC-based websites.
Description
Quantitative analysis of user-generated content on the Web - Web Science Overlay Journal (demo)
%0 Generic
%1 ieKey
%A Ochoa, Xavier
%A Duval, Erik
%B Proceedings of the First International Workshop on Understanding Web Evolution (WebEvolve 2008)
%D 2008
%K analysis content prosumer quality user_genereated_content web web2.0
%P 19-26
%T Quantitative analysis of user-generated content on the Web
%X User-generated content (UGC) is becoming the most popular and valuable information available on the WWW. However, little serious research has been conducted to measure the properties of its production process. This paper presents an in-depth quantitative analysis of 9 popular websites that are based on different UGC types. The Information Production Process is used as a framework for the analysis. The findings provide for first time strong scientific evidence for previously anecdotic knowledge: UGC production follows “long-tail” distributions and it is marked with a strong “participation inequality”. Also, the analysis arrived to unexpected findings: not all the UGC types follow the inverse power-law distribution, and large content collections could be dominated by the presence of ultraproductive users. The analysis results also have implications for the administration of UGC-based websites.
%@ 978 085432885 7
@misc{ieKey,
abstract = {User-generated content (UGC) is becoming the most popular and valuable information available on the WWW. However, little serious research has been conducted to measure the properties of its production process. This paper presents an in-depth quantitative analysis of 9 popular websites that are based on different UGC types. The Information Production Process is used as a framework for the analysis. The findings provide for first time strong scientific evidence for previously anecdotic knowledge: UGC production follows “long-tail” distributions and it is marked with a strong “participation inequality”. Also, the analysis arrived to unexpected findings: not all the UGC types follow the inverse power-law distribution, and large content collections could be dominated by the presence of ultraproductive users. The analysis results also have implications for the administration of UGC-based websites.},
added-at = {2008-04-27T14:23:51.000+0200},
author = {Ochoa, Xavier and Duval, Erik},
biburl = {https://www.bibsonomy.org/bibtex/2da696cbf929c158cc0a9d5132f7a137f/bluedolphin},
booktitle = {Proceedings of the First International Workshop on Understanding Web Evolution (WebEvolve 2008)},
date = {22 April 2008},
description = {Quantitative analysis of user-generated content on the Web - Web Science Overlay Journal (demo)},
interhash = {40cf10589d289f3a0a86c7364124ddb3},
intrahash = {da696cbf929c158cc0a9d5132f7a137f},
isbn = {978 085432885 7},
keywords = {analysis content prosumer quality user_genereated_content web web2.0},
location = {Beijing, China},
month = {April},
pages = {19-26},
timestamp = {2008-04-27T14:25:25.000+0200},
title = {Quantitative analysis of user-generated content on the Web },
year = 2008
}