Comprehensive Study on Sentiment Analysis: Types, Approaches, Recent Applications, Tools and APIs

Binju Saju, Siji Jose, Amal Antony
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引用次数: 5

Abstract

Sentiment analysis can be considered a major application of machine learning, more particularly natural language processing (NLP). As there are varieties of applications, Sentiment analysis has gained a lot of attention and is one among the fastest growing research area in computer science. It is a type of data analysis which is observed from news reports, user reviews, feedbacks, social media updates etc. Responses are collected and analyzed by researchers. All sentiments can be classified into three categories-Positive, Negative and Neutral. The paper gives a detailed study of sentiment analysis. It explains the basics of sentiment analysis, its types, and different approaches of sentiment analysis. The recent tools and APIs along with various real world applications of sentiment analysis in various areas are also described briefly.
情感分析的综合研究:类型、方法、最新应用、工具和api
情感分析可以被认为是机器学习的主要应用,尤其是自然语言处理(NLP)。随着应用的多样化,情感分析受到了广泛的关注,是计算机科学中发展最快的研究领域之一。这是一种从新闻报道、用户评论、反馈、社交媒体更新等方面观察到的数据分析。研究人员收集和分析这些反馈。所有的情绪都可以分为三类——积极的、消极的和中性的。本文对情感分析进行了详细的研究。它解释了情感分析的基础,它的类型,和不同的情感分析方法。本文还简要介绍了最近的工具和api以及情感分析在各个领域的各种实际应用。
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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