Sentiment Analysis Based on Emotion Commonsense Knowledge
YANG Liang1, ZHOU Fengqing1, LIN Hongfei1, YIN Fuliang2, ZHANG Yiming1
1.School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China; 2.School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
Abstract：With the rapid development of artificial intelligence in recent years, the demand for commonsense know-ledge has become more and more urgent. As a part of commonsense knowledge, emotion commonsense knowledge is also an important aspect of affective computing. In view of the limitations in the structure and content of the emotion dictionary, we present an emotion commonsense library of binary structure. To construct the library, the set of emotion commonsense knowledge candidates is obtained through knowledge extraction, followed by manual annotation and automatic expansion. Experimental results on opening datasets show that the binary emotion commonsense library constructed in this paper improves the precision of sentiment analysis.
[1] Medhat W,Hassan A ,Korashy H .Sentiment analysis algorithms and applications:A survey[J].Ain Shams Engineering Journal,2014,5(4):1093-1113. [2] Liu B.Sentiment analysis and opinion mining[J].Synthesis Lectures on Human Language Technologies,2012,5(1):1-167. [3] Fellbaum C.WordNet:An electronic lexical database[J].Library Quarterly Information Community Policy,1998,25(2):292-296. [4] Liu H,Singh P.ConceptNet—a practical commonsense reasoning tool-kit[J].BT Technology Journal,2004,22(4):211-226. [5] 柳位平,朱艳辉,栗春亮,等.中文基础情感词词典构建方法研究[J].计算机应用,2009,29(10):2875-2877. [6] 杨超,冯时,王大玲,等.基于情感词典扩展技术的网络舆情倾向性分析[J].小型微型计算机系统,2010,31(4):691-695. [7] 周咏梅,杨佳能,阳爱民.面向文本情感分析的中文情感词典构建方法[J].山东大学学报 (工学版),2013,43(6):27-33. [8] 赵妍妍,秦兵,刘挺.文本情感分析[J].软件学报,2010,21(8):1834-1848. [9] Esuli A,Sebastiani F.SentiWordNet:A publicly available lexical resource for opinion mining[C]//Proceedings of the 5th Conference on Language Resources and Evaluation,2006:417-422. [10] Ku LW,Lo YS,Chen HH.Using polarity scores of words for sentence-level opinion extraction[C]//Proceedings of NTCIR-6 Workshop Meeting.2007,316-322. [11] 徐琳宏,林鸿飞,潘宇,等.情感词汇本体的构造[J].情报学报,2008,27(2):180-185. [12] Mikolov T ,Sutskever I ,Chen K ,et al.Distributed representations of words and phrases and their compositionality[C]//Proceedings of Advances in Neural Information Processing Systems,2013,26:3111-3119. [13] Pennington J,Socher,R Manning C D.GloVe:Global vectors for word representation[C]//Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing.2014:1532-1543. [14] Cortes C,Vapnik V.Support-vector networks[J].Machine Learning,1995,20(3):273-297. [15] Hochreiter S,Schmidhuber J.Long short-term memory[J].Neural Computation,1997,9(8):1735-1780. [16] Krizhevsky A,Sutskever I,Hinton G E.Imagenet classification with deep convolutional neural networks[C]//Proceedings of Advances in Neural Information Processing Systems.2012:1097-1105. [17] Bahdanau D,Cho K H,Bengio Y.Neural machine translation by jointly learning to align and translate[J].arXiv preprint,arXiv:1409.0473,2014. [18] Giatsoglou M ,Vozalis M G ,Diamantaras K ,et al.Sentiment analysis leveraging emotions and word embeddings[J].Expert Systems with Applications,2017,69:214-224. [19] 冯兴杰,张志伟,史金钏.基于卷积神经网络和注意力模型的文本情感分析[J].计算机应用研究,2018,35(5):1434-1436. [20] Songbo Tan,Jin Zhang.An empirical study of sentiment analysis for Chinese documents[J].Expert Systems with Applications,2008,34(4):2622-2629. [21] Li S,Zhao Z,Hu R,et al.Analogical reasoning on Chinese morphological and semantic relations[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics,2018:138-143.
2019, Vol. 33 
