介绍用户生成内容(UGC)的源流发展,并在此基础上引入信息生产过程理论(IPP)的视角,介绍其基本概念及其数理表达形式,并从理论角度和模拟实证角度探讨IPP 应用于UGC 的可行性.通过8 个不同类型的UGC 网站开展实证研究,包括:Flickr 、Delicious 、Youku 、YouTube 、Amazon 、Fan Fiction 、CiteULike 、Yahoo!知识堂.根据不同的数据采集规则采集相关元数据并进行数据分析,包括描述性统计、累积分布函数分析以及数据分布拟合,在IPP 视角下从定量的角度揭示UGC 的特征与机理,如UGC 的离散分布与集中趋势、UGC 的帕累托最优表现、UGC 中长尾理论的特征、UGC 的自相似性及粒度分析等,试图从理论上揭示UGC 的生成规律,为研究相关UGC 动因做好前期准备,并为UGC 运营商提供相关激励机制设计的参考依据和辅助决策.%This paper first introduces the origin and development of user-generated content, and then explains the foundation and mathematical form of Information Production Process ( IPP) . Based on the theory and practice of the two, the paper studies the feasibility of applying the IPP as a framework to guide the research of UGC. The authors take an empirical study to reveal the characters and mechanisms of UGC quantitatively by collecting data from 8 UGC sites based on different rules, which included the law of scattering distribution, Pateto rules, long tail theory and self-similarity, etc. Finally the authors conduct a discussion to explore the incentive mechanism of UGC in terms of its character based on IPP perspective.
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