情感分析的综合调查

S. Rajalakshmi, S. Asha, N. Pazhaniraja
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引用次数: 17

摘要

社会媒体数据在组织中被有效地用于在用户中获得人气。在这里,每个用户都可以分享他们对不同事物的看法(如产品视图、一般问题等)。在这种情况下,情感分析或观点挖掘对于从这些数据中挖掘事实很有用。从社交网络中获取的文本数据主要进行情感挖掘,以检验用户消息的情感。大多数情绪或情感挖掘使用机器学习方法来获得更好的结果。这篇文章背后的主要思想是提出情感分析所涉及的过程。进一步的调查是关于执行情感分析的各种方法或技术。它还介绍了用于演示情感分析过程的各种工具。本文报告了情感分析中存在的机遇和问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comprehensive survey on sentiment analysis
Social media data are effectively used in organizations to gain popularity among its users. Here each user can share their ideas about different things (i.e. product views, general issues and so on.)In this case, sentiment analysis or opining mining is useful for mining facts from those data. The text data obtained from the social network primarily undergoes emotion mining to examine the sentiment of the user message. Most of the sentiment or emotional mining uses machine learning approaches for better results. The principle idea behind this article is to bring out the process involved in sentiment analysis. Further the investigation is about the various methods or techniques existing for performing sentiment analysis. It also presents the various tools used to demonstrate the process involved in sentiment analysis. This article reports about the opportunities and issues existing in the sentiment analysis.
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