基于在线评论的网络视频情感分类平台设计与实现
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摘要
基于读者情感分析模型对网络视频情感分类时,未能计算在线评论的情感相似性,仅能分类新闻书评类的网络视频情感,存在一定局限性。设计基于在线评论的网络视频情感分类平台,根据HowNet的语义共同点获取观点词同褒义词和贬义词的语义共同点,确定观点词的情感极性,通过基于在线评论的网络视频的情感程度与否定副词判断情感强度,采用在线评论情感相似性计算方法计算情感极性和情感强度得出最终情感得分,通过情感得分分类网络视频情感。实验结果表明,当在线评论中基准词的取值为10对时,所设计平台可实现最佳情感极性的判断结果,该平台对于积极情感和消极情感平均分类正确率都达到98%、平均分类召回率都低于10%。
The emotional similarity of online reviews cannot be calculated,and only the online video emotions of news book reviews can be classified when the reader emotional analysis model is used to conduct emotional classification of network videos,which has a certain limitations. Therefore,a network video emotional classification platform based on online comments is designed. The semantic commonalities between opinion words versus with commendatory words and derogatory words are ob-tained according to the semantic commonalities of HowNet,so as to determine the emotional polarities of opinion words. The emotional intensities are judged according to the emotional degrees and negative adverbs of network videos based on online com-ments. The emotional similarity calculation method based on online comments is adopted to calculate emotional polarities and in-tensities,so as to obtain the final emotional score. The network video emotions are classified according to the emotional score.The experimental results show that the designed platform can obtain the optimal emotional polarity judgment results when the value of benchmark words in online reviews is 10 pairs,and has an average classification accuracy of 98%,and an average classifica-tion recall rate less than 10% for both positive and negative emotions.
The emotional similarity of online reviews cannot be calculated,and only the online video emotions of news book reviews can be classified when the reader emotional analysis model is used to conduct emotional classification of network videos,which has a certain limitations. Therefore,a network video emotional classification platform based on online comments is designed. The semantic commonalities between opinion words versus with commendatory words and derogatory words are ob-tained according to the semantic commonalities of HowNet,so as to determine the emotional polarities of opinion words. The emotional intensities are judged according to the emotional degrees and negative adverbs of network videos based on online com-ments. The emotional similarity calculation method based on online comments is adopted to calculate emotional polarities and in-tensities,so as to obtain the final emotional score. The network video emotions are classified according to the emotional score.The experimental results show that the designed platform can obtain the optimal emotional polarity judgment results when the value of benchmark words in online reviews is 10 pairs,and has an average classification accuracy of 98%,and an average classifica-tion recall rate less than 10% for both positive and negative emotions.
引文
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[5]令狐新荣.多媒体网络负面信息分类方法研究与仿真[J].计算机仿真,2016,33(8):260-263.LINGHU Xingrong.Based on multimedia network negative information model of optimizing SVM classification method research[J].Computer simulation,2016,33(8):260-263.
[6]洪庆,王思尧,赵钦佩,等.基于弹幕情感分析和聚类算法的视频用户群体分类[J].计算机工程与科学,2018,40(6):1125-1139.HONG Qing,WANG Siyao,ZHAO Qinpei,et al.Video user group classification based on barrage comments sentiment analysis and clustering algorithms[J].Computer engineering and science,2018,40(6):1125-1139.
[7]邓扬,张晨曦,李江峰.基于弹幕情感分析的视频片段推荐模型[J].计算机应用,2017,37(4):1065-1070.DENG Yang,ZHANG Chenxi,LI Jiangfeng.Video shot recommendation model based on emotion analysis using time-sync comments[J].Journal of computer applications,2017,37(4):1065-1070.
[8]林平荣,侯志,文贵华.基于深度学习的情感识别开放平台[J].计算机工程与设计,2016,37(6):1510-1514.LIN Pingrong,HOU Zhi,WEN Guihua.Open platform of emotion recognition based on deep learning[J].Computer engineering and design,2016,37(6):1510-1514.
[9]冯多,林政,付鹏,等.基于卷积神经网络的中文微博情感分类[J].计算机应用与软件,2017,34(4):157-164.FENG Duo,LIN Zheng,FU Peng,et al.Chinese micro-blog emotion classification based on CNN[J].Computer applications and software,2017,34(4):157-164.
[10]侯德林,赵丽平,张星,等.网络视频服务用户内容传播行为意愿实证研究[J].管理评论,2015,27(11):86-95.HOU Delin,ZHAO Liping,ZHANG Xing,et al.Empirical study on intention of user content dissemination behavior in network video services[J].Management review,2015,27(11):86-95.