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New Technology of Library and Information Service  2012, Vol. Issue (9): 69-74    DOI: 10.11925/infotech.1003-3513.2012.09.12
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A Method for Network Opinion Modeling Based on Governmental Public Decision Domain
Deng Shasha1,2, Zhang Pengzhu1, Li Xinmiao3
1. Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai 200052, China;
2. School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
3. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China
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Abstract  This paper designs a framework of network opinion modeling based on governmental public decision, which includes data preparation and network opinion modeling. Guided by the framework, it analyzes the case of completing medical care system, and the successful application validates the effectiveness of the proposed framework.
Key wordsNetwork opinion      Public decision      Text mining      Chinese information processing     
Received: 15 May 2012      Published: 25 December 2012
: 

G202

 
  TP391

 

Cite this article:

Deng Shasha, Zhang Pengzhu, Li Xinmiao. A Method for Network Opinion Modeling Based on Governmental Public Decision Domain. New Technology of Library and Information Service, 2012, (9): 69-74.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2012.09.12     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2012/V/I9/69

[1] 金兼斌. 网络舆论调查的方法和策略[J]. 河南社会科学, 2007, 15(4): 118-121.(Jin Jianbin. Approaches and Strategies of Online Opinion Investigation[J]. Henan Social Sciences, 2007, 15(4): 118-121.)
[2] Wattal S, Schuff D, Mandviwalla M, et al. Web 2.0 and Politics: The 2008 U.S. Presidential Election and an E-politics Research Agenda[J]. MIS Quarterly, 2010, 34(4): 669-688.
[3] Zhang K, Zi J, Wu G L. New Event Detection Based on Indexing-tree and Named Entity[C]. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’07), Amsterdam. New York: ACM, 2007: 215-222.
[4] Kim S M, Hovy E. Determining the Sentiment of Opinions[C]. In: Proceedings of the 20th International Conference on Computational Linguistics(COLING’04), Geneva. Stroudsburg: Association for Computational Linguistics, 2004: 1367-1373.
[5] 金珠, 林鸿飞,赵晶. 基于HowNet的话题跟踪及倾向性分类研究[J]. 情报学报, 2005, 24(5): 555-561.(Jin Zhu, Lin Hongfei, Zhao Jing. Study on Topic Tracking and Tendency Classification Based on HowNet [J]. Journal of the China Society for Scientific and Technical Information, 2005, 24(5): 555-561.)
[6] 张卫, 曹先彬, 尹洪章. 基于多特征融合的聊天室社会网络挖掘方法[J]. 中国科学技术大学学报, 2009, 39(5): 540-546.(Zhang Wei, Cao Xianbin, Yin Hongzhang. Chat Room Social Network Mining Based on Multi-features Fusion[J]. Journal of University of Science and Technology of China, 2009, 39(5): 540-546.)
[7] Dave K, Lawrence S, Pennock D M. Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews [C]. In: Proceedings of the 12th International Conference on Word Wide Web(WWW’03), Budapest. New York: ACM, 2003:519-528.
[8] Liu B, Hu M Q, Chen J S. Opinion Observer: Analyzing and Comparing Opinion on the Web[C]. In: Proceedings of the 14th International Conference on Word Wide Web(WWW’05), Chiba. New York: ACM, 2005:342-351.
[9] 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.(Yang Chao, Feng Shi, Wang Daling, et al. Analysis on Web Public Opinion Orientation Based on Extending Sentiment Lexicon[J]. Mini-micro Systems, 2010, 31(4):691-695.)
[10] 吴渝, 杨涛, 肖开洲. BBS突发舆情分析及基于小世界网络的预测模型[J]. 重庆邮电大学学报:自然科学版, 2010, 22(3): 350-354.(Wu Yu, Yang Tao, Xiao Kaizhou. Analysis of Emergent BBS Sentiment and Its Prediction Model Based on Small World Network[J]. Journal of Chongqing University of Posts and Telecommunications: Natural Science Edition, 2010, 22(3): 350-354.)
[11] 钱爱兵. 基于主题的网络舆情分析模型及其实现[J]. 现代图书情报技术, 2008(4):49-55.(Qian Aibing. A Model for Analyzing Public Opinion Under the Web and Its Implementation [J]. New Technology of Library and Information Service, 2008(4):49-55.)
[12] O’Leary D E. Blog Mining-review and Extensions: “From Each According to His Opinion” [J]. Decision Support Systems, 2011, 51(4): 821-830.
[13] 洪宇, 张宇, 刘挺, 等. 话题检测与跟踪的评测及研究综述[J]. 中文信息学报, 2007, 21(6): 71-87.(Hong Yu, Zhang Yu, Liu Ting, et al. Topic Detection and Tracking Review[J]. Journal of Chinese Information Processing, 2007, 21(6): 71-87.)
[14] Lam W, Meng H M L, Wong K L, et al. Using Contextual Analysis for News Event Detection[J]. International Journal on Intelligent Systems, 2001, 16(4):525-546.
[15] 于满泉, 骆卫华, 许洪波,等. 话题识别与跟踪中的层次化话题识别技术研究[J]. 计算机研究与发展, 2006, 43(3): 489-495.(Yu Manquan, Luo Weihua, Xu Hongbo, et al. Research on Hierarchical Topic Detection in Topic Detection and Tracking[J]. Journal of Computer Research and Development, 2006, 43(3): 489-495.)
[16] Liu T, Ma J S, Zhu H J, et al. Dependency Parsing Based on Dynamic Local Optimization[C]. In: Proceedings of the 10th Conference on Computational Natural Language Learning(CoNLL-X’06), Stroudsburg: Association for Computational Linguistics, 2006: 211-215.
[17] 胡鞍钢. 中国特色的公共决策民主化——以制定“十二五”规划为例[J]. 清华大学学报:哲学社会科学版, 2011, 26(2): 43-50.(Hu Angang. The Democratization of Public Policy Making with Chinese Characteristic: Formulation of the China’s 12th Five-Year Plan[J]. Journal of Tsinghua University:Philosophy and Social Sciences, 2011, 26(2): 43-50.)
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