面向情绪分类的情绪词向量学习

doi:10.6040/j.issn.1671-9352.1.2016.072

山东大学学报（理学版） ›› 2017, Vol. 52 ›› Issue (7): 52-58.doi: 10.6040/j.issn.1671-9352.1.2016.072

面向情绪分类的情绪词向量学习

杜漫,徐学可,杜慧,伍大勇,刘悦,程学旗

中国科学院网络数据科学与技术重点实验室, 中国科学院计算技术研究所, 北京 100190

收稿日期:2016-11-25 出版日期:2017-07-20 发布日期:2017-07-07
作者简介:杜漫(1991— ),女,硕士研究生,研究方向为自然语言理解的情感和情绪分类研究.E-mail:duman@ict.ac.cn

Emotion-specific word embedding learning for emotion classification

DU Man, XU Xue-ke, DU Hui, WU Da-yong, LIU Yue, CHENG Xue-qi

CAS Key Lab of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

Received:2016-11-25 Online:2017-07-20 Published:2017-07-07

摘要/Abstract

摘要： 提出了一种面向情绪分类的融合词内部信息和情绪标签的词向量学习方法。在CBOW模型的基础上,引入词内部成分和情绪标签信息,以适应微博情绪表达的不规范,同时丰富词向量的情绪语义。对于输入文本,按照词的TF-IDF权重对词向量进行加权求和,以作为文本向量表示。以上述词向量或文本向量作为情绪分类器的输入,采用机器学习的分类方法(LR、SVM、CNN),验证本文情绪词向量在情绪分类任务上的实验效果。实验表明,情绪词向量与原始CBOW词向量相比,在准确率、召回率、F值等各项指标上都有更好的表现。

关键词: 情绪分类, 情绪分析, 词内部信息, 情绪标签, 词向量

Abstract: We present a method for emotion classification based on word vector learning which considering the inner patterns and emotion labels of words. Based on the CBOW model, we introduce the inner patterns and the emotion label, in order to enrich the emotional semantics of the word vectors. For one input document, according to the TF-IDF weight of the word, we use the weighted linear combination as the text representation. We use the word vectors or text vectors as the input of the emotion classifier, using machine learning classification method(LR, SVM, CNN), to verify the experimental results in emotion classification task. Experiments show that the presented algorithm performs better than CBOW model.

Key words: word embedding, emotion analysis, emotion labels, emotion classification, word inner pattern

中图分类号:

TP391.1

杜漫,徐学可,杜慧,伍大勇,刘悦,程学旗. 面向情绪分类的情绪词向量学习[J]. 山东大学学报（理学版）, 2017, 52(7): 52-58.

DU Man, XU Xue-ke, DU Hui, WU Da-yong, LIU Yue, CHENG Xue-qi. Emotion-specific word embedding learning for emotion classification[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(7): 52-58.

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面向情绪分类的情绪词向量学习

Emotion-specific word embedding learning for emotion classification

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