一种混合语种文本的多维度多情感分析方法  

A Multi-Dimensional and Multi-Emotion Analysis Method for Mixed Language Texts

作　　者：李妍慧 郑超美[1] 王炜立[1] 杨昕 LI Yanhui;ZHENG Chaomei;WANG Weili;YANG Xin(College of Information and Engineering,Nanchang University,Nanchang 330031,China)

机构地区：[1]南昌大学信息工程学院,南昌330031

出　　处：《计算机工程》2020年第12期113-119,141,共8页Computer Engineering

基　　金：江西省自然科学基金(20161BAB212040)。

摘　　要：针对中英混合微博文本情感分析问题,提出一种新的多维度多情感分析方法。将中英混合语言文本分别翻译成中文和英文,提取文本在不同语言维度的特征,基于中英混合语言、中文、英文分别提取对应的语义信息,综合上述3种从不同语言维度获取的语义信息,构建一个多情感分类模型并进行训练微调,根据情感概率得到最终的分类结果。实验结果表明,相比单一的处理方法,该方法能够更全面地提取中英混合文本的语义特征,并精准地判别文本中的多种情感,具有较好的分类效果。To address the emotion analysis of Chinese-English code-mixed microblog texts,this paper proposes a new multi-dimensional and multi-emotion analysis method.The Chinese-English code-mixed texts are translated into Chinese and English respectively,and features of the texts in different language dimensions are extracted.Then the corresponding semantic information is extracted based on the Chinese-English mixed language,Chinese and English.By combining the three kinds of semantic information extracted from different language dimensions,a multi-emotion classification model is constructed and trained for fine tuning.Finally,the classification result is obtained based on the emotional probability.Experimental results show that compared with simple processing methods,the proposed method more comprehensively extracts the semantic features of Chinese-English code-mixed texts,accurately distinguishes multiple emotions in the text,and has a better classification effect.

关 键 词：中英混合微博 多情感分析 多维度方法 BERT模型 迁移学习 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]