基于LS-SO算法的情感文本分类方法
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摘要
首先,基于点互信息与信息检索(PMI-IR)算法,提出一种Laplace平滑情感判定(LS-SO)算法,对情感词典与表情符号情感词典进行自动扩充,得到了具有一定规模、高质量的情感词典,包括基础情感词典、目标情感词典、网络用语情感词典、表情符号情感词典、否定词词典、疑问词词典、程度副词词典和连词词典.其次,通过细化文本语义分析规则计算文本情感值.实验结果验证了该方法的有效性.
Firstly,based on the pointwise mutual information-information retrieval(PMI-IR)algorithm, we proposed Laplace smoothing-sentiment opinion(LS-SO) algorithm, which automatically expanded the emotional dictionary and the emotional dictionary of emotive symbols.A certain scale and high quality emotional dictionary was obtained,including basic emotional dictionary,target emotional dictionary,online emotional dictionary,emotional dictionary of emotive symbols,negative dictionary,interrogative dictionary,degree adverb dictionary,conjunction dictionary.Then,the emotional value of text was calculated by refining the rules of text semantic analysis.The experimental results verified the effectiveness of the proposed method.
Firstly,based on the pointwise mutual information-information retrieval(PMI-IR)algorithm, we proposed Laplace smoothing-sentiment opinion(LS-SO) algorithm, which automatically expanded the emotional dictionary and the emotional dictionary of emotive symbols.A certain scale and high quality emotional dictionary was obtained,including basic emotional dictionary,target emotional dictionary,online emotional dictionary,emotional dictionary of emotive symbols,negative dictionary,interrogative dictionary,degree adverb dictionary,conjunction dictionary.Then,the emotional value of text was calculated by refining the rules of text semantic analysis.The experimental results verified the effectiveness of the proposed method.
引文
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[2]陈国兰.基于情感词典和语义规则的微博情感分析[J].情报探索,2016(2):1-6.(CHEN Guolan.Microblog Sentiment Analysis Basing on Emotion Dictionary and Semantic Rule[J].Information Research,2016(2):1-6.)
[3]郑诚,沈磊,代宁.基于类序列规则的中文微博情感分类[J].计算机工程,2016,42(2):184-189.(ZHENG Cheng,SHEN Lei,DAI Ning.Chinese Microblog Emotion Classification Based on Class Sequential Rules[J].Computer Engineering,2016,42(2):184-189.)
[4]王文,王树锋,李洪华.基于文本语义和表情倾向的微博情感分析方法[J].南京理工大学学报,2014,38(6):733-738.(WANG Wen,WANG Shufeng,LI Honghua.Microblogging Sentiment Analysis Method Based on Text Semantics and Expression Tendentiousness[J].Journal of Nanjing University of Science and Technology,2014,38(6):733-738.)
[5]夏梦南.中文微博情感倾向性分析与情感要素抽取方法[D].北京:北京工业大学,2015.(XIA Mengnan.Method of Chinese Microblog Sentiment Analysis and Sentiment Element Extraction[D].Beijing:Beijing University of Technology,2015.)
[6]侯敏,滕永林,李雪燕,等.话题型微博语言特点及其情感分析策略研究[J].语言文学应用,2013(2):135-143.(HOU Min,TENG Yonglin,LI Xueyan,et al.Study on the Linguistic Features of the Topic-Oriented Microblog and the Strategies for Its Sentiment Analysis[J].Applied Linguistics,2013(2):135-143.)
[7]王斌.面向微博的观点摘要关键技术研究[D].太原:山西大学,2015.(WANG Bin.Research on the Key Technologies of Opinion Summarization Facing the Micro-blog[D].Taiyuan:Shanxi University,2015.)
[8]肖江,丁星,何荣杰.基于领域情感词典的中文微博情感分析[J].电子设计工程,2015,23(12):18-21.(XIAOJiang,DING Xing,HE Rongjie.Analysis of Chinese Micro-blog Emotion Which Based on Field of Emotional Dictionary[J].Electronic Design Engineering,2015,23(12):18-21.)