大众分类法对信息过载的影响及优化策略研究——以豆瓣网为例  

The Effect and Optimization Strategy of Folkonomy Research on the Information Overload——Take Douban. com for Example

作　　者：王娜[1] 田晓蒙 

机构地区：[1]郑州大学信息管理学院,河南郑州450001

出　　处：《现代情报》2016年第9期74-81,87,共9页Journal of Modern Information

基　　金：国家社会科学基金项目"泛在网络中的信息过载与信息组织模式研究"(项目编号:12CTQ027)研究成果之一

摘　　要：[目的/意义]调研显示,大众分类法是造成豆瓣网中信息过载的主要原因,但国内尚未发现针对性研究。[方法/过程]通过问卷星调研大众分类法对豆瓣网中信息过载的影响,并利用SPSS、EXCEL等软件对搜集的数据进行分析、整理。[结果/结论]通过分析数据得出以下主要结论:豆瓣网中的分类体系不能满足用户基本需要;大众分类法在豆瓣网中的应用存在多种问题,如同义词标签过多和标签专指度不高等。在此基础上,本文提出了一种优化大众分类法的策略,并探讨了其实施方案。[Purpose/Significance] The research showed that Folksonomy was the main reason for causing the information overload in Douban.com, but it was not yet found a targeted research in domestic. [Methods/Process] Researched the effect of Folksonomy for information overload in Douban by Questionnaire Star, and used SPSS mad EXCEL＇ to analyze and sort collected data. [ Result/Conclusion] By analyzing data this paper draw the following conclusions： the classification system in Douban could not meet the basic needs of users; the application of Folksonomy in Douban existed kinds of problems, such as too many synonyms tags and low specificity tags. And on this basis, this paper put forward a Folksonomy optimization strategy and discussed its implementation.

关 键 词：大众分类法 豆瓣网 信息过载 标签优化 

分 类 号：G254.1[文化科学—图书馆学]