A practical approach to Sentiment Analysis of hindi tweets

Y. Sharma, V. Mangat, Mandeep Kaur
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引用次数: 36

Abstract

Sentiment Analysis(SA) is a combination of emotions, opinions and subjectivity of text. Today, social networking sites like Twitter are tremendously used in expressing the opinions about a particular entity in the form of tweets which are limited to 140 characters. Reviews and opinions play a very important role in understanding peoples satisfaction regarding a particular entity. Such opinions have high potential for knowledge discovery. The main target of SA is to find opinions from tweets, extract sentiments from them and then define their polarity, i.e, positive, negative or neutral. Most of the work in this domain has been done for English Language. In this paper, we discuss and propose sentiment analysis using Hindi language. We will discuss an unsupervised lexicon method for classification.
印地语推文情感分析的实用方法
情感分析是对文本的情感、观点和主观性的综合分析。今天,像Twitter这样的社交网站被大量用于以tweet的形式表达对特定实体的意见,这些tweet限制在140个字符以内。评论和意见在了解人们对特定实体的满意度方面起着非常重要的作用。这些观点具有很大的知识发现潜力。SA的主要目标是从tweet中找到观点,从中提取情感,然后定义它们的极性,即积极,消极或中性。这个领域的大部分工作都是针对英语语言完成的。在本文中,我们讨论并提出了使用印地语的情感分析。我们将讨论一种用于分类的无监督词典方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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