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Review on Sentiment Analysis of Indian Languages with a Special Focus on Code Mixed Indian Languages

机译:审查印度语言的情感分析,特别关注混合代码印度语言

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摘要

Given the wide applicability of social media platforms, individuals increasingly turn to the web to seek and share information, opinions, comments and suggestions which results in proliferation of user generated large volume of text data available for interpretation. A large number of users in India write their feelings or emotions in more than one language, thereby a large volume of text data is made available for Natural Language Processing (NLP) researchers. Sentiment Analysis (SA) of code-mixed text provides useful information in the field of politics, marketing, business, health, sports and what not. During the past decade the work on Sentiment Analysis of Indian language textual data, particularly in Hindi has got momentum in contrast to code-mixed Indian language text. However, due to non-availability of language and vocabulary (linguistic and lexical) tools and annotated resources, the task of Sentiment Analysis of Indian Languages becomes somehow difficult. In this study an attempt has been made to provide a detailed summary of Sentiment Analysis of Indian languages with a special focus on code mixed Indian Languages.
机译:鉴于社交媒体平台的广泛适用性,个人越来越多地转向Web寻求和共享信息,意见,评论和建议,这导致用户生成的大量文本数据可用于解释的数量激增。印度的大量用户使用一种以上的语言来书写他们的感受或情感,因此自然语言处理(NLP)研究人员可以获得大量的文本数据。混合代码文本的情感分析(SA)在政治,市场营销,商业,卫生,体育以及其他方面提供有用的信息。在过去的十年中,与代码混合的印度语言文本相比,印度语言文本数据(尤其是印地语)情感分析工作得到了发展。但是,由于无法使用语言和词汇(语言和词汇)工具以及注释资源,印度语言的情感分析任务变得有些困难。在这项研究中,已尝试提供印度语言情感分析的详细摘要,特别着重于混合代码印度语言。

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