A survey on sentiment classification algorithms, challenges and applications

IF 0.3 Q4 COMPUTER SCIENCE, THEORY & METHODS Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI:10.2478/ausi-2018-0004
Muhammad Rizwan Rashid Rana, Asif Nawaz, J. Iqbal
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引用次数: 6

Abstract

Abstract Sentiment classification is the process of exploring sentiments, emotions, ideas and thoughts in the sentences which are expressed by the people. Sentiment classification allows us to judge the sentiments and feelings of the peoples by analyzing their reviews, social media comments etc. about all the aspects. Machine learning techniques and Lexicon based techniques are being mostly used in sentiment classification to predict sentiments from customers reviews and comments. Machine learning techniques includes several learning algorithms to judge the sentiments i.e Navie bayes, support vector machines etc whereas Lexicon Based techniques includes SentiWordnet, Wordnet etc. The main target of this survey is to give nearly full image of sentiment classification techniques. Survey paper provides the comprehensive overview of recent and past research on sentiment classification and provides excellent research queries and approaches for future aspects
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情感分类算法、挑战及应用综述
情感分类是对人们在句子中所表达的情感、情绪、观念和思想进行挖掘的过程。情绪分类可以让我们通过分析人们的评论、社交媒体评论等来判断人们的情绪和感受。机器学习技术和基于Lexicon的技术主要用于情感分类,以预测客户评论和评论的情绪。机器学习技术包括几种判断情感的学习算法,如Navie bayes,支持向量机等,而基于词典的技术包括SentiWordnet, Wordnet等。本调查的主要目标是给出情感分类技术的近乎完整的图像。调查论文提供了近期和过去的情绪分类研究的全面概述,并为未来的方面提供了优秀的研究问题和方法
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来源期刊
Acta Universitatis Sapientiae Informatica
Acta Universitatis Sapientiae Informatica COMPUTER SCIENCE, THEORY & METHODS-
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发文量
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