一种情感判别分析体系在汽车品牌舆情管理中的应用

doi:10.11959/j.issn.2096-0271.2017061

Abstract

Abstract:

Brand public opinion management involves text,voice and other natural language processing,such as mining the emotions and views of the text and quantifies it.The quantification of emotion in natural language is the emotion discriminant analysis.Considering the disadvantage in the traditional sentiment analysis that based on emotional dictionary and supervision model based sentiment analysis system,a new sentiment analysis system was proposed,and combined with the Naive Bayesian classification algorithm,the accuracy of sentiment analysis was improved,and the ability of quantitative analysis of emotional strength was enhanced.The sentiment discrimination accuracy of the proposed text sentiment analysis engine is higher than that of the common analysis method,and there is no decent of accuracy in out-ofsample texts from different industries.

Key words: sentiment analysis, supervised model, naive Bayes, natural language processing

CLC Number:

TP391

Yunsheng SONG. Application of an emotion discriminant analysis system in the management of automobile brand[J]. Big Data Research, 2017, 3(6): 55-64.

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References 19

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情感词	类型
哀艳	1
安顿	1
爱不忍释	1
赞助	1
责任	1
阿Q	1
暗弱	-1
昂贵	-1
浅陋	-1

情感词	在正向文本中的DF（pDF）	在负向文本中的DF（nDF）
哀艳	0.000 255 102	8.430 28E-5
安顿	0.000 340 136	0.000 590 12
爱不忍释	0.000 255 102	8.430 28E-5
赞助	8.503 4E-5	8.430 28E-5
责任	0.001 530 612	0.003 877 93
阿Q	0.000 255 102	8.430 28E-5
暗弱	8.503 4E-5	0.000 337 211
昂贵	0.000 680 272	0.000 421 514
浅陋	8.503 4E-5	0.000 337 211

程度副词	权重
略微	0.8
稍微	0.8
非常	2
极端	2
至极	2

文本	情感词	在正向文本中的DF（pDF）	在负向文本中的DF（nDF）
我非常不喜欢喝茶	喜欢	0.02	0.1

情感词	正向情感得分	负向情感得分
喜欢	0.051 161 3	0.009 133 5
保养贵	0.000 020 8	0.001 808 3
乱七八糟	0.000 541 6	0.001 164 7
发疯	0.000 041 7	0.000 122 6
创新	0.000 312 5	0.000 245 2
渗油	0.000 020 8	0.001 409 9
漏油	0.000 020 8	0.002 114 8
…	…	…

Application of an emotion discriminant analysis system in the management of automobile brand

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