基于语义情感空间模型的新浪微博情感分析

Huang He
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引用次数: 18

摘要

随着Web 2.0的飞速发展,越来越多的人开始在互联网上发布自己的信息或个人意见。微博的应用满足了人们的需求,为人们提供了一个实时发布和互动的公共平台。随着微博更新量的快速增长,大量信息和情感复杂数据在微博平台上发布,微博的研究越来越受到人们的关注,尤其是一个持续的热点话题——短信情感分析。到目前为止,中国的微博探索还有很多工作要做。本文以新浪微博的情感分析为研究对象,提出了三种微博定向分类方法来解决微博情感分析问题,并对每种分类方法的准确率和性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment analysis of Sina Weibo based on semantic sentiment space model
With the rapid development of Web 2.0, more and more people begin to publish information or their custom opinions on the Internet. Micro-blog's application satisfies people's need and provides a public platform for people to post and interact in real time. As a result of the rapidly increasing number of micro-blog updates, a lot of information and emotions complex data release in this platform, researches on micro-blog have attracted more and more attention, especially, one continuous heat topic, sentiment analysis of short message. So far, Chinese micro-blog exploration still needs lots of further work. Focus on Sina Weibo's sentiment analysis, the key of this paper is to put forward three methods of Micro-Blog orientation classification to resolve the problem of Micro-Blog sentiment analysis, and compare the accuracy and performance of each classification method.
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