Please wait a minute...
Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (4): 53-62    DOI: 10.11925/infotech.2096-3467.2018.1069
Current Issue | Archive | Adv Search |
Research on Weibo Opinion Leaders Identification and Analysis in Medical Public Opinion Incidents
Jiang Wu1,2(),Yinghui Zhao1,Jiahui Gao1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Center for E-commerce Research and Development, Wuhan University, Wuhan 430072, China
Download: PDF (3227 KB)   HTML ( 12 ) 
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper aims to identify Weibo opinion leaders and study their influence in medical public opinion incidents. [Methods] This article integrates user personal attributes, network characteristics, behavioral characteristics and text features to construct a comprehensive index system to identify opinion leaders in different periods of medical public opinion incidents, and also use time difference correlation analysis to study the impact of the emotional tendency of opinion leaders on the public sentiment. [Results] Taking the 2018 vaccine event as a case, this paper verifies the effectiveness of the proposed opinion leader identification model. The results show that the medical public opinion hotspots and the types of opinion leaders differ in different periods, and the attitudes of opinion leaders have a guiding effect on the emotions of the general public. [Limitations] We only examined the performance on the proposed methods with the vaccine event data and the model generalization ability remains underdeveloped. [Conclusions] The multi-feature opinion leader identification method proposed in this paper can better discover potential opinion leaders among grassroots users compared with traditional evaluation indicators.
Key words： Medical Public Opinion      Opinion Leader      Clustering Analysis      Time Difference Correlation Analysis      Text Analysis     
Received: 26 September 2018      Published: 29 May 2019
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Jiang Wu
Yinghui Zhao
Jiahui Gao

Cite this article:

Jiang Wu,Yinghui Zhao,Jiahui Gao. Research on Weibo Opinion Leaders Identification and Analysis in Medical Public Opinion Incidents. Data Analysis and Knowledge Discovery, 2019, 3(4): 53-62.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.1069     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I4/53

[1] 陈立富, 王兰成, 王果. 医疗机构网络舆情原因分析与应对策略[J]. 解放军医院管理杂志, 2014, 21(1): 35-37.
[1] (Chen Lifu, Wang Lancheng, Wang Guo.Cause Analysis and Strategies on Dealing with Network Opinion in Medical Institutions[J]. Hospital Administration Journal of Chinese People's Liberation Army, 2014, 21(1): 35-37.)
[2] 王佳敏, 吴鹏, 陈芬, 等. 突发事件中意见领袖的识别和影响力实证研究[J]. 情报学报, 2016, 35(2): 169-176.
[2] (Wang Jiamin, Wu Peng, Chen Fen, et al.Empirical Study on Recognition and Influence of Opinion Leaders in Emergency[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(2): 169-176.)
[3] Asur S, Huberman B A, Szabo G, et al.Trends in Social Media: Persistence and Decay[C]// Proceedings of the 5th International AAAI Conference on Weblogs and Social Media. 2011.
[4] 晏敬东, 杨彩霞, 张炜南. 基于生命周期理论的微博舆情引控研究[J]. 情报杂志, 2017, 36(8): 88-93.
[4] (Yan Jingdong, Yang Caixia, Zhang Weinan.Study on the Control and Guidance of Micro-Blog Public Opinion Based on the Lifecycle Theory[J]. Journal of Intelligence, 2017, 36(8): 88-93.)
[5] Lazarsfeld P F, Berelson B, Gaudet H.The People's Choice[M]. Oxford, England: Duell, Sloan & Pearce, 1944.
[6] Rogers E M.Diffusion of Inovations[M]. The 5th Edition. Free Press, 2003.
[7] Katz E, Lazarsfeld P F, Roper E.Personal Influence: The Part Played by People in the Flow of Mass Communications[M]. Routledge, 2005.
[8] Chan K K, Misra S.Characteristics of the Opinion Leader: A New Dimension[J]. Journal of Advertising, 1990, 19(3): 53-60.
[9] Bond R M, Fariss C J, Jones J J, et al.A 61-Million-Person Experiment in Social Influence and Political Mobilization[J]. Nature, 2012, 489: 295-298.
[10] Rogers E M, Cartano D G.Methods of Measuring Opinion Leadership[J]. Public Opinion Quarterly, 1962, 26(3): 435-441.
[11] Jonnalagadda S, Peeler R, Topham P.Discovering Opinion Leaders for Medical Topics Using News Articles[J]. Journal of Biomedical Semantics, 2012, 3: 2.
[12] Zhao K, Greer G E, Yen J, et al.Leader Identification in an Online Health Community for Cancer Survivors: A Social Network-based Classification Approach[J]. Information Systems and E-Business Management, 2015, 13(4): 629-645.
[13] 陈远, 刘欣宇. 基于社会网络分析的意见领袖识别研究[J]. 情报科学, 2015, 33(4): 13-19, 92.
[13] (Chen Yuan, Liu Xinyu.Research on Opinion Leaders Recognition Based on Social Network[J]. Information Science, 2015, 33(4): 13-19, 92.)
[14] Weng J, Lim E P, Jiang J, et al.TwitterRank: Finding Topic-Sensitive Influential Twitterers[C]// Proceedings of the 3rd ACM International Conference on Web Search and Data Mining, New York, USA. ACM, 2010: 261-270.
[15] 肖宇, 许炜, 商召玺. 微博用户区域影响力识别算法及分析[J]. 计算机科学, 2012, 39(9): 38-42.
[15] (Xiao Yu, Xu Wei, Shang Zhaoxi.Analysis on Algorithms of Identifying Regional Influential Users in Micro-blogging[J]. Computer Science, 2012, 39(9): 38-42.)
[16] Zhou H, Zeng D, Zhang C.Finding Leaders from Opinion Networks[C]// Proceedings of the 2009 IEEE International Conference on Intelligence and Security Informatics. IEEE, 2009: 266-268.
[17] 熊涛, 何跃. 微博转发网络中意见领袖的识别与分析[J]. 现代图书情报技术, 2013(6): 55-62.
[17] (Xiong Tao, He Yue.The Identification and Analysis of Micro-blogging Opinion Leaders in the Network of Retweet Relationship[J]. New Technology of Library and Information Service, 2013(6): 55-62.)
[18] Pal A, Counts S.Identifying Topical Authorities in Microblogs[C]// Proceedings of the 4th ACM International Conference on Web Search and Data Mining, Hong Kong, China. ACM, 2011: 45-54.
[19] 彭丽徽, 李贺, 张艳丰. 基于灰色关联分析的网络舆情意见领袖识别及影响力排序研究——以新浪微博“8·12滨海爆炸事件”为例[J]. 情报理论与实践, 2017, 40(9): 90-94.
[19] (Peng Lihui, Li He, Zhang Yanfeng.Research on the Identification and Influence Ranking of Network Public Opinion Leaders Based on Grey Relational Analysis[J]. Information Studies: Theory & Application, 2017, 40(9): 90-94.)
[20] 陈芬, 陈佩帆, 吴鹏, 等. 融合用户特征与多级文本倾向性分析的网络意见领袖识别[J]. 情报理论与实践, 2018, 41(7): 143-148.
[20] (Chen Fen, Chen Peifan, Wu Peng, et al.Online Opinion Leader Identification Method Integrating User Feature and Multilevel Text Sentiment Analysis[J]. Information Studies: Theory & Application, 2018, 41(7): 143-148.)
[21] Valente T W.Network Models of the Diffusion of Innovations[J]. Computational & Mathematical Organization Theory, 1996, 2(2): 163-164.
[22] Watts D J.A Simple Model of Global Cascades on Random Networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(9): 5766-5771.
[23] Matsumura N, Ohsawa Y, Ishizuka M.Influence Diffusion Model in Text-Based Communication[J]. Transactions of the Japanese Society for Artificial Intelligence, 2002, 17(3): 259-267.
[24] 樊兴华, 赵静, 方滨兴, 等. 影响力扩散概率模型及其用于意见领袖发现研究[J]. 计算机学报, 2013, 36(2): 360-367.
[24] (Fan Xinghua, Zhao Jing, Fang Binxing, et al.Influence Diffusion Probability Model and Utilizing It to Identify Network Opinion Leader[J]. Chinese Journal of Computers, 2013, 36(2): 360-367.)
[25] Coleman J, Katz E, Menzel H.The Diffusion of an Innovation Among Physicians[J]. Sociometry, 1957, 20(4): 253-270.
[26] Coulter R A, Feick L F, Price L L.Changing Faces: Cosmetics Opinion Leadership Among Women in the New Hungary[J]. European Journal of Marketing, 2002, 36(11/12): 1287-1308.
[27] Kwak H, Lee C, Park H, et al.What is Twitter, a Social Network or News Media?[C]// Proceedings of the 19th International Conference on World Wide Web. ACM, 2010: 591-600.
[28] Cha M, Haddadi H, Benevenuto F, et al.Measuring User Influence in Twitter: The Million Follower Fallacy[C]// Proceedings of the 4th International AAAI Conference on Weblogs and Social Media. 2010.
[29] Ren J, Cheng Z, Shen J, et al.Influences of Influential Users: An Empirical Study of Music Social Network[C]// Proceedings of the 2014 International Conference on Internet Multimedia Computing and Service. ACM, 2014: 411.
[30] 张米, 张晖, 杨春明, 等. 基于多特征信息传播模型的微博意见领袖挖掘[J]. 中文信息学报, 2018, 32(2): 129-138.
[30] (Zhang Mi, Zhang Hui, Yang Chunming, et al.Microblog Opinion Leader Mining Based on a Multi-feature Information Diffusion Model[J]. Journal of Chinese Information Processing, 2018, 32(2): 129-138.)
[31] Kleinberg J M.Authoritative Sources in a Hyperlinked Environment[J]. Journal of the ACM, 1999, 46(5):604-632.
[32] 卢永春. “让违法者倾家荡产”成为网民的高频词[EB/OL]. (2018-07-27). [2018-09-10].http://yuqing.people.com.cn/ n1/2018/0727/c209043-30174707.html
[32] (Lu Yongchun. “Let the Lawbreakers Go Bankrupt” has Become High-Frequency Words in Netizens[EB/OL]. (2018-07-27). [2018-09-10]. http:// yuqing.people.com.cn/n1/2018/0727/c209043-30174707.html
[33] 易承志. 群体性突发事件网络舆情的演变机制分析[J]. 情报杂志, 2011, 30(12): 6-12.
[33] (Yi Chengzhi.Analysis on the Changing Mechanism of Mass Emergency Network Public Opinion[J]. Journal of Intelligence, 2011, 30(12): 6-12.)
[34] Mikolov T, Chen K, Corrado G, et al.Efficient Estimation of Word Representations in Vector Space[OL]. arXiv Preprint, arXiv: 1301.3781.
[35] Wieting J, Bansal M, Gimpel K, et al.Towards Universal Paraphrastic Sentence Embeddings[OL]. arXiv Preprint, arXiv: 1511.08198.
[36] Blei D M, Ng A Y, Jordan M I.Latent Dirichlet Allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022.
[37] Shannon C E.A Mathematical Theory of Communication[J]. Bell Labs Technical Journal, 1948, 27(3): 379-423.
[38] Ku L W, Liang Y T, Chen H H. Opinion Extraction, Summarization and Tracking in News and Blog Corpora[C]// Proceedings of the 20th International AAAI Conference, 2006.
[39] Gyamfi Y, Wiebe J, Mihalcea R, et al.Integrating Knowledge for Subjectivity Sense Labeling[C]// Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics. 2009: 10-18.
[40] Yang S L, Li Y S, Hu X X, et al.Optimization Study on K Value of K-means Algorithm[J]. Systems Engineering- Theory & Practice, 2006, 26(2): 97-101.
[1] Chen Jun,Liang Hao,Qian Chen. Studying Investment Decisions of Rewarded Crowdfunding Users with Emotional Distance and Text Analysis[J]. 数据分析与知识发现, 2021, 5(4): 60-71.
[2] Xu Yabin, Sun Qiutian. Identifying Leaders and Dissemination Paths of Public Opinion[J]. 数据分析与知识发现, 2021, 5(2): 32-42.
[3] Hyonil Kim,Ou Shiyan. Identifying Citation Texts with Unsupervised Method[J]. 数据分析与知识发现, 2021, 5(1): 66-77.
[4] Wu Jinming,Hou Yuefang,Cui Lei. Automatic Expression of Co-occurrence Clustering Based on Indexing Rules of Medical Subject Headings[J]. 数据分析与知识发现, 2020, 4(9): 133-144.
[5] Tian Zhonglin,Wu Xu,Xie Xiaqing,Xu Jin,Lu Yueming. Real-time Analysis Model for Short Texts with Relationship Graph of Domain Semantics[J]. 数据分析与知识发现, 2020, 4(2/3): 239-248.
[6] Fen Chen,Xiaohuan Gao,Yue Peng,Yuan He,Chunxiang Xue. Identifying Weibo Opinion Leaders with Text Sentiment Analysis[J]. 数据分析与知识发现, 2019, 3(11): 120-128.
[7] Chengzhi Zhang,Zheng Li. Extracting Sentences of Research Originality from Full Text Academic Articles[J]. 数据分析与知识发现, 2019, 3(10): 12-18.
[8] Yu Yan,Zhao Naixuan. Weighted Topic Model for Patent Text Analysis[J]. 数据分析与知识发现, 2018, 2(4): 81-89.
[9] Chen Fen,Fu Xi,He Yuan,Xue Chunxiang. Identifying Weibo Opinion Leaders with Social Network Analysis and Influence Diffusion Model[J]. 数据分析与知识发现, 2018, 2(12): 60-67.
[10] He Yue,Zhu Can. Sentiment Analysis of Weibo Opinion Leaders——Case Study of “Illegal Vaccine” Event[J]. 数据分析与知识发现, 2017, 1(9): 65-73.
[11] Ma Tianyi,Zhang Pengzhu,Feng Haoyin. Knowledge Requirement Model for Online Outsourcing Tasks[J]. 现代图书情报技术, 2016, 32(3): 74-81.
[12] Li Gang, Ye Guanghui, Zhang Yan. Feature Recognition of Niche Expert——Empirical Analysis Based on MetaFilter Dataset[J]. 现代图书情报技术, 2015, 31(6): 71-77.
[13] Xiong Tao, He Yue. The Identification and Analysis of Micro-blogging Opinion Leaders in the Network of Retweet Relationship[J]. 现代图书情报技术, 2013, (6): 55-62.
[14] Teng Guangqing,Bi Qiang. Market Segmentation of Digital Library Users Based on Concept Lattice ——Conceptual Clustering Analysis of Digital Library Users[J]. 现代图书情报技术, 2010, 26(2): 7-11.
[15] Wang Cuiying(Compiler). Study on Tag Clustering Analysis[J]. 现代图书情报技术, 2008, 24(5): 67-71.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626，82624938   E-mail:jishu@mail.las.ac.cn