摘要
【目的】分析电子商务中现有产品评价模式的不足,提出一种改进不足的产品评价新模式。【方法】在国内最大的微博平台上,针对某一产品主题抽取1 687条微博数据,并采用文本情感分类技术,对该样本数据集进行建模和分析。【结果】分析面向产品主题的微博数据,对其蕴含的语义信息进行归纳总结,发现其同样具有产品整体评价功能。并由于微博数据生成的自发性,其分析结果更具有客观性。【局限】更大规模样本数据的分析没有全面涉及,基于微博的动态产品评价研究没有涉及。【结论】该模式可以在一定程度上克服原有互联网产品评价模式的弱点,从而吸引更多企业关注微博产品评价信息。
[Objective] Analyze the existing product evaluation models of electronic commerce, find their shortages, and propose a new model to improve these shortages. [Methods] Collect 1 687 microblogging data on a product from the largest microblogging platform in China. Analyze and build modeling on the sample data sets by text sentimental classification. [Results] Analyzing the microblogging data on a product and summarizing their inherent semantic information. The research find that they can be used to evaluate product characterisics. And these data is generated with spontaneous, so the results of the analysis are more objective. [Limitations] Analysis of a larger sample of data is not fully involved, also the evaluation of products based on dynamic mieroblogging data is not involved. [Conclusions] The analysis in the paper indicates that this model overcomes the weakness of original ones to a certain extent; accordingly, it attracts more companies＇ attention on microblogging product evaluation infnrmatian
出处
《现代图书情报技术》
CSSCI
北大核心
2014年第4期92-98,共7页
New Technology of Library and Information Service
基金
北京市自然科学基金项目"基于多源信息融合的北京公共危机事件情境感知研究"(项目编号:9142014)的研究成果之一
关键词
微博
情感分析
众包
产品评价
Microblogging Sentiment analysis Crowdsourcing Product evaluation
