[1]ZHANG Donghui,CHENG Xianyi.Research on computation of affect in public opinion sentences from the cognition viewpoint[J].CAAI Transactions on Intelligent Systems,2017,12(4):498-503.[doi:10.11992/tis.201607023]
Copy

Research on computation of affect in public opinion sentences from the cognition viewpoint

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 12 Number of periods: 2017 4 Page number: 498-503 Column: 学术论文—自然语言处理与理解 Public date: 2017-08-25
Title:
Research on computation of affect in public opinion sentences from the cognition viewpoint
Author(s):
ZHANG Donghui1;  CHENG Xianyi2
1. Computing Center, Beijing Information Science & Technology University, Beijing 100192, China;
2. School of Computer Science and Technology, Nantong University, Nantong 226019, China
Keywords:
cognitive; sentiment computer; public opinion sentence; energy of view; active; negative; semantic; coarse-grained; fine granularity
CLC:
TP391.1
DOI:
10.11992/tis.201607023
Abstract:
The current viewpoint analysis method is limited to the traditional text analysis technology, whereby a public opinion sentence can only be divided into positive and negative poles and the extent of each pole (coarse-grained) determined. It is difficult to determine whether a public opinion sentence is active or passive. In this paper, we discuss a computation framework for fine-grained semantic sentiments from the cognitive science viewpoint and propose a quantitative analysis method for public opinion sentences. This method takes the text collection of some topic as input and uses a real number to represent the energy of a viewpoint in the text. We conducted an experiment using the Natural Language Processing and Information Retrieval (NLPIR) sharing platform and a contrasting experiment with respect to view recognition by comparing coarse-grained and fine-grained affects. The experimental results show that the two methods have the same recognition performance regarding sentence viewpoints. For no-opinion sentences, the fine-grained method performs better than the coarse-grained method.
References:
[1] MCKEOWN G, VALSTAR M F, COWIE R, et al. The SEMAINE corpus of emotionally colored character interactions[C]//Proceedings of IEEE International Conference on Multimedia and Expo, ICME 2010. IEEE Computer Society, 2010:1079-1084.
[2] 徐琳宏,林鸿飞.认知视角下的文本情感计算[J]. 计算机科学, 2010, 37(12):182-185.XU Linhong, LIN Hongfei. Text affective computing from cognitive perspective[J]. Computer science, 2010, 37(12):182-185.
[3] 任巨伟,杨亮,林鸿飞.情感图式构造及其在文本情感计算中的应用[J].江西师范大学学报:自然科学版, 2013, 37(2):130-136.REN Juwei,YANG Liang, LIN Hongfei. The construc-tion of affective schemata and its application in text affective computing[J]. Journal of Jiangxi normal university:natural science, 2013, 37(2):130-136.
[4] PETRANTONAKIS P C, HADJILEONTIADIS L J. A novel emotion elicitation index using frontal brain asymmetry for enhanced eeg-based emotion recognition[J]. IEEE transactions on information technology in biomedicine, 2011, 15(5):737-746.
[5] 宋静静. 中文短文本情感倾向性分析研究[D].重庆:重庆理工大学, 2013.SONG Jingjing. Research on Chinese short-text sentiment analysis[D]. Chongqing:Chongqing University of Technology, 2013.
[6] 程显毅,刘颖. 基于知识图的观点句识别算法研究[J].计算机科学, 2015, 2015. 42(6):123-129.CHENG Xianyi, LIU Ying. Research on algorithm of perspective sentence identification based on knowledge map[J]. Computer science, 2015, 42(6):123-129.
[7] 蔡艳婧,程晓红,程显毅. 网络敏感信息动态特征的抽取方法[J]. 常州大学学报, 2014, 16(4):80-86.CAI Yanjing, CHENG Xiaohong, CHENG Xianyi. Research on algorithm of network sensitive inforamtion features extracting[J]. Journal of changzhou university:natural science edition, 2014, 16(4):80-86.
[8] 王志良.人工心理与人工情感[J].智能系统学报, 2006, 1(1):38-44.WANG Zhiliang. Artificial psychology and artificial emotion[J]. CAAI transactions on intelligent systems, 2006, 1(1):38-44.
[9] 齐鑫.网络民意对我国政府决策的影响[D].沈阳:东北大学, 2010.QI Xin. The influence of net citizen on government decision-making in China[D]. Shenyang:Northeastern University, 2010.
[10] 史杨. 网络舆情与公共政策议程的设置[J].云南电大学报, 2011, 13(3):55-59.SHI Yang. Setting of internet public opinion and public policy agenda[J]. Journal of Yunnan RTV university, 2011, 13(3):55-59.
[11] 孙浩博,侯军岐. 论我国互联网种业发展[J]. 价值工程, 2016, 37(9):327-329.SUN Haobo, HOU Junqi. On the development of China’s seed industry based on internet[J]. Value engineering, 2016, 37(9):327-329.
[12] 高云棋. 基于主题模型的舆情分析子系统研究与设计[D]. 成都:电子科技大学, 2013.GAO Yunqi. Research and development of opinion mining sub-system based on topic model[D]. Chengdu:University of Electronic Science and Technology of China, 2013.
[13] 史继林,朱英贵.褒义词词典[M].成都:四川辞书出版社, 2006:23-28.SHI Jilin, ZHU Yinggui. The commendatory word dictionary[M]. ChengDu:Sichuan publishers of Lexicogr-aphical, 2006:23-28.
[14] 杨玲,朱英贵. 贬义词词典[M]. 成都:四川辞书出版社, 2006:15-35.YANG Ling, Zhu Yinggui. Derogatory term dictionary[M]. Sichuan publishers of Lexicogr-aphical, 2006:15-35.
[15] 董振东.知网的情感词典[EB/OL]. (2007-10-22)[2013-12-20]. http://www.keenage.com/html/c_bulletin_2007.htm. DONGhendong.Hownetdictionary[EB/OL]. (2007-10-22)[2013-12-20]. http://www.keenage.com/html/c_bulletin_2007.htm
[16] rongzhe. NTUSD[EB/OL].台湾:台北大学,(2013-8-2)[2014.11-21]. http://www.datatang.com/data/11837.rongzhe. NTUSD[EB/OL]. Taiwan:Taipei university, (2013-8-2)[2014.11-21].http://www.datatang.com/data/11837.
[17] 王晓东,王娟,张征. 基于情感词汇本体的主观性句子倾向性计算[J]. 计算机应用, 2012, 32(6):1678-1681.WANG Xiaodong, WANG Juan, ZHANG Zheng. Computation on orientation for subjective sentence based on sentiment words ontology[J]. Journal of computer applications, 2012, 32(6):1678-1681.
[18] 张华平. NLPIR微博关注关系语料库1000万条[EB/OL]. (2013-10-23)[2014-11-2].http://www.datatang.com/data/14350. ZHANG Huaping. NLPIR Weibo focused on relationship between corpus of 10 million,[EB/OL].(2013-10-23)[2014-11-2].http://www.datatang.com/data/14350.
[19] 中国计算机学会.中文微博情感分析评测结果[EB/OL]. 北京:北京大学. (2012-11-2)[2014-9-22].http://tcci.ccf.org. cn/conference/2012/pages/page04_evares. html.CCF.Chinese microblog sentiment analysis evaluation results[EB/OL]. Peiking:Peiking university. (2012-11-2)[2014-9-22]. http://tcci.ccf.org.cn/conference/2012/pages/page04_evares.html.
[20] 林慧恩,林世平.中文情感倾向分析中主观句子抽取方法的研究[C]//全国第20届计算机技术与应用学术会议(CACIS·2009)暨全国第1届安全关键技术与应用学术会议论文集(上册). 上海, 2009:379-383.LIN Huien, Lin Shiping. Research on extracting subjective sentence in chinese sentiment orientation analysis[C]//Conference CACIS·2009. Shanhai, China, 2009:379-383.
Similar References:

Memo

-

Last Update: 2017-08-25

Copyright © CAAI Transactions on Intelligent Systems