On-site Impression Grasping System Using SNS Location Information and Sentiment Analysis

Ryosuke Yamano, Thatsanee Charoenporn, Virach Sornlertlamvanich
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Abstract

In the recent years, information from such as Social Networking Service (SNS) is overflowing. It draws a great attention from research community in efficiently collecting and analyzing what is being shared in real time. Extracting topics in SNS and analyzing the emotional expression related to those topics are one of the means to know the trends of social interest. In the conventional sentiment analysis, the sentiment of a sentence is estimated on a word-by-word basis, which tends to give undesired results. In many cases, such as negative auxiliary verbs, adverbs, and adjectives related to emotional words are ignored in configurating the emotional expressions. In this research, a method of natural language processing (NLP) in sentiment analysis is performed phrase by phrase by combining the results of active text analysis with the location information. We propose a method to grasp the social impression on an event by improving the phrase level sentiment analysis combining to the location information.
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基于SNS位置信息和情感分析的现场印象抓取系统
近年来,来自社交网络服务(SNS)等的信息层出不穷。如何有效地收集和分析实时共享的内容,已引起了研究界的广泛关注。从社交网络中提取话题,分析与话题相关的情感表达,是了解社交兴趣趋势的手段之一。在传统的情感分析中,一个句子的情感是基于一个词一个词的基础上估计的,这往往会得到不希望得到的结果。在很多情况下,与情感词相关的否定助动词、副词、形容词等在配置情感表达时往往被忽略。本研究将活动文本分析结果与位置信息相结合,逐句进行情感分析中的自然语言处理(NLP)。我们提出了一种结合地点信息对短语级情感分析进行改进的方法来把握事件的社会印象。
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