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New Technology of Library and Information Service  2014, Vol. 30 Issue (2): 72-78    DOI: 10.11925/infotech.1003-3513.2014.02.10
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Research on Public Opinion of the Disputes on Huangyan Island in the Network News:A Case Study of “Special Reports about the Disputes Between China and Philippines on Huangyan Island”on Sina
Zou Wei1,3, Liu Yongxue1,2, Li Manchun1,2, Wang Jiasheng1,3, Chen Yingxue3
1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China;
2. Collaborative Innovation Center for the South China Sea Studies, Nanjing 210023, China;
3. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
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Abstract  

[Objective] Depending on "Special Reports about the Disputes between China and Philippines on Huangyan Island"on Sina, the study explores the situation and correlation of the disputes between China and Philippines on Huangyan Island. [Context] With the rapid development of the Internet, it has been the main carrier of reflecting social hot spot. The disputes between China and Philippines on Huangyan Island in 2012 is a typical events on public opinions. To obtain a comprehensive understanding of events, the study searches the public opinions of the events effectively and reasonably. [Methods] This study uses the methods of Web crawler to get the news data, employs text participle to obtain the elements of news and establishes database of the disputes of Huangyan Island. By using mathematical statistics and Gephi software, the study achieves data analysis. [Results] Changing processes of the situation in the disputes between China and Philippines on Huangyan Island can be divided into five stages. It accords with the lifecycle principle of network public sentiment emergency. The focus in the disputes between China and Philippines on Huangyan Island is similar, but the two sides focused on different measures. [Conclusions] This study is helpful to show a complete development process of the disputes between China and Philippines on Huangyan Island. Meanwhile, it also performs different measures and standpoints between China and Philippines on Huangyan Island.

Key wordsHuangyan Island      Public opinion      Network news      Sina      Gephi     
Received: 09 October 2013      Published: 06 March 2014
:  G35  

Cite this article:

Zou Wei, Liu Yongxue, Li Manchun, Wang Jiasheng, Chen Yingxue. Research on Public Opinion of the Disputes on Huangyan Island in the Network News:A Case Study of “Special Reports about the Disputes Between China and Philippines on Huangyan Island”on Sina. New Technology of Library and Information Service, 2014, 30(2): 72-78.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.02.10     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I2/72

[1] 戴超. 国内主流网站"黄岩岛事件"舆论建构策略研究[J]. 新闻世界, 2012(12): 84-85. (Dai Chao. Domestic Mainstream Website"Huangyan Island Incident" Public Opinion Construction Strategy Research[J]. News World, 2012(12): 84-85.)
[2] 中国互联网络信息中心. 第31次中国互联网络发展状况统计报告[EB/OL].[2013-01-15]. http://www. cnnic. net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201301/t20130115_38508.htm. (CNNIC. The 31st Statistic Report of China Internet Network Development[EB/OL].[2013-01-15]. http://www.cnnic.net. cn/hlwfzyj/hlwxzbg/hlwtjbg/201301/t20130115_38508.htm.)
[3] 赵华, 赵铁军, 张姝, 等. 基于内容分析的话题检测研究[J]. 哈尔滨工业大学学报, 2006, 38(10): 1740-1743. (Zhao Hua, Zhao Tiejun, Zhang Shu, et al. Topic Detection Research Based on Content Analysis[J]. Journal of Harbin Institute of Technology, 2006, 38(10): 1740-1743.)
[4] 王伟, 许鑫. 基于聚类的网络舆情热点发现及分析[J]. 现代图书情报技术, 2009(3): 74-79. (Wang Wei, Xu Xin. Online Public Opinion Hotspot Detection and Analysis Based on Document Clustering[J]. New Technology of Library and Information Service, 2009(3): 74-79.)
[5] 童亚拉, 彭江. 群智能在网络舆情热点发现及研判机制中的应用分析[J]. 电脑学习, 2010(4): 128-129. (Tong Yala, Peng Jiang. The Analysis of Applying Swarm Intelligence to Cyberspace Public Opinion's Hotspot Discovery and Pre-warning Mechanism[J]. Computer Study, 2010(4): 128-129.)
[6] 任海果. 基于主题事件的舆情分析系统的设计与实现[D]. 北京: 北京邮电大学, 2012. (Ren Haiguo. The Design and Implementation of Public Opinion Analysis System Based on Topic Events[D]. Beijing: Beijing University of Posts and Telecommunications, 2012.)
[7] Allan J, Carbonell J G, Doddington G, et al. Topic Detection and Tracking Pilot Study Final Report[C]. In: Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop. 1998: 194-218.
[8] Li F, Du T C. Who is Talking? An Ontology-Based Opinion Leader Identification Framework for Word-of-Mouth Marketing in Online Social Blogs[J]. Decision Support Systems, 2011, 51(1): 190-197.
[9] UMBC eBiquity. BlogVox: Separating Blog Wheat from Blog Chaff[EB/OL].[2011-08-01]. http://ebiquity. umbc. edu/paper/html/id/326/BlogVox-Separating-Blog-Wheat-from-Blog-Chaff.
[10] Neri F, Aliprandi C, Capeci F, et al. Sentiment Analysis on Social Media[C]. In: Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE Computer Society, 2012: 919-926.
[11] 刘晓东. 基于内容分析的新浪新闻平台研究[J]. 情报杂志, 2009, 28(S1): 1-4. (Liu Xiaodong. Research of Sina News Platform Based on the Content Analysis[J]. Journal of Intelligence, 2009, 28(S1): 1-4.)
[12] 易前良, 奚流. 新浪、网易网络新闻比较分析[J]. 新闻界, 2007(1): 20-21. (Yi Qianliang, Xi Liu. Comparative Analysis of Network News Between Sina and Netease[J]. Press Circles, 2007(1): 20-21.)
[13] Alexa. Traffic Detail (sina. com. cn)[EB/OL].[2013-07-10]. http://www. alexa. com/siteinfo/sina. com. cn#trafficstats.
[14] 新浪新闻. 中菲黄岩岛争端专题[EB/OL].[2012-04-11]. http://news. sina. com. cn/z/zfnh2012/. (Sina News. Topic of the Disputes on Huangyan Island[EB/OL].[2012-04-11]. http://news. sina. com. cn/z/zfnh2012/.)
[15] 金应忠, 倪世雄. 国际关系理论比较研究[M]. 北京: 中国社会科学出版社, 1992. (Jin Yingzhong, Ni Shixiong. A Comparative Study of International Relations Theory[M]. Beijing: China Social Sciences Press, 1992.)
[16] 新浪新闻. 菲律宾今日再向南海黄岩岛海域派海岸警卫队船[EB/OL].[2012-04-12]. http://news. sina. com. cn/c/2012-04-12/131124261248. shtml. (Sina News. Today Philippines Sends Coast Guard's Boats to Huangyan Island in the South China Sea Again[EB/OL].[2012-04-12]. http//news.sina.com.cn/c/2012-04-12/131124261248. shtml.)
[17] Levene M. An Introduction to Search Engines and Web Navigation[M]. John Wiley & Sons, 2011.
[18] LocoySpider[EB/OL].[2013-07-10]. http://www.locoy.com/.
[19] CodePlex. 盘古分词[EB/OL].[2013-07-10]. http://pangusegment.codeplex.com/. (CodePlex. Pan Gu Segment[EB/OL].[2013-07-10]. http://pangusegment.codeplex.com/.)
[20] Gephi[EB/OL].[2013-07-10]. http://gephi.org/.
[21] Hu Y. Algorithms for Visualizing Large Networks[J]. Combinatorial Scientific Computing, 2011, 5(3): 180-186.
[22] 谢科范, 赵湜, 陈刚, 等. 网络舆情突发事件的生命周期原理及集群决策研究[J]. 武汉理工大学学报: 社会科学版, 2010, 23(4): 482-486. (Xie Kefan, Zhao Shi, Chen Gang, et al. Research on Lifecycle Principle and Group Decision-making of Network Public Sentiment Emergency[J]. Journal of Wuhan University of Technology: Social Sciences Edition, 2010, 23(4): 482-486.)

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