Selection of Users’ Behaviors Towards Different Topics of Microblog on Public Health Emergencies
Lu An1,Yanping Liang2()
1Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China 2School of Information Management, Wuhan University, Wuhan 430072, China
[Objective] This paper aims to reveal the relationship between topics of microblog and user behaviors at different stages of public health emergencies. [Methods] We analyzed the behavioral patterns among different topics and within a specific topic. The LDA topic model improved by the relevance formula was employed to extract the topics of microblog entries on public health emergencies. The cosine distances between microblog topics and the numbers of retweets, comments, favorites, as well as those between each pair of behavior counts, were calculated to explore users’ behavior patterns towards the same or different topics. [Results] During public health emergencies, the evolutionary trends of users’ behaviors of retweets, comments, favorites are roughly similar. Significant correlations exist between the counts of three behaviors. The correlation coefficients between the counts of retweets and comments, those of comments and favorites, and those of retweets and favorites are 0.390, 0.274, 0.180 respectively. Microblogs related to the topics of event progress, government responses and knowledge dissemination are more likely to be commented on, while those related to the topics of public opinions and event measures are more likely to be retweeted. [Limitations] The universality of the conclusion is subject to the examination of other cases. [Conclusions] The tendency of user behaviors towards different types of topics is obviously unequal, which means different behaviors may happen among different topics and within a specific topic.
安璐,梁艳平. 突发公共卫生事件微博话题与用户行为选择研究*[J]. 数据分析与知识发现, 2019, 3(4): 33-41.
Lu An,Yanping Liang. Selection of Users’ Behaviors Towards Different Topics of Microblog on Public Health Emergencies. Data Analysis and Knowledge Discovery, 2019, 3(4): 33-41.
Blei D M, Ng A Y, Jordan M I.Latent Dirichlet Allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022.
[2]
Liu X, Burns A C, Hou Y.An Investigation of Brand-Related User-Generated Content on Twitter[J]. Journal of Advertising, 2017, 46(2): 236-247.
[3]
Panasyuk A, Yu E S L, Mehrotra K G. Controversial Topic Discovery on Members of Congress with Twitter[J]. Procedia Computer Science, 2014, 36: 160-167.
[4]
Karami A, Dahl A A, Turner-Mcgrievy G, et al.Characterizing Diabetes, Diet, Exercise, and Obesity Comments on Twitter[J]. International Journal of Information Management, 2018, 38(1): 1-6.
[5]
Zhao W X, Jiang J, Weng J, et al.Comparing Twitter and Traditional Media Using Topic Models[C]// Proceedings of the 33rd European Conference on Information Retrieval. 2011: 338-349.
[6]
Ramage D, Dumais S T, Liebling D J.Characterizing Microblogs with Topic Models[C]// Proceedings of the 4th International AAAI Conference on Weblogs and Social Media. 2010: 130-137.
[7]
Blei D M, Lafferty J D.Dynamic Topic Models[C]// Proceedings of the 23rd International Conference on Machine Learning. ACM, 2006: 113-120.
[8]
Lau J H, Collier N, Baldwin T.On-line Trend Analysis with Topic Models: #twitter Trends Detection Topic Model Online[C]// Proceedings of the 2012 International Conference on Computational Linguistics. 2012: 1519-1534.
[9]
Zhao H, Liu G, Shi C, et al.A Retweet Number Prediction Model Based on Followers’ Retweet Intention and Influence[C]// Proceedings of the 2014 IEEE International Conference on Data Mining Workshop. IEEE, 2015: 952-959.
[10]
马莹莹. 微博用户转发行为及情感预测研究[D]. 哈尔滨: 哈尔滨工业大学, 2015.
[10]
(Ma Yingying.Research on Prediction of Retweeting Behaviors and Sentiment on Microblog[D]. Harbin: Harbin Institute of Technology, 2015.)
(Tang Xiaobo, Luo Yingli.Integrating Emotional Divergence and User Interests into the Prediction of Microblog Retweeting[J]. Library and Information Service, 2017, 61(9): 102-110.)
(Meng Jijie.An Empirical Study on the Government Microblog Released in Emergencies —— “Shanghai City” Microblog as an Example[D]. Shanghai: Shanghai Jiaotong University, 2014.)
[13]
Qu Y, Huang C, Zhang P, et al.Microblogging After a Major Disaster in China: A Case Study of the 2010 Yushu Earthquake[C]// Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work, 2011: 25-34.
[14]
Burkholder B T, Toole M J.Evolution of Complex Disasters[J]. The Lancet, 1995, 346(8981): 1012-1015.
[15]
Fink S.Crisis Management: Planning for the Inevitable[M]. New York: American Management Association, 1986: 20.
[16]
Turner B A.The Organizational and Interorganizational Development of Disasters[J]. Administrative Science Quarterly , 1976, 21(3): 378-397.
(Liu Zhiming, Liu Lu.Public Negative Emotion Model in Emergencies Based on Aging Theory[J]. Journal of Industrial Engineering and Engineering Management, 2013, 27(1): 15-21.)
[20]
Sievert C, Shirley K E.LDAvis: A Method for Visualizing and Interpreting Topics[C]// Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces. 2014: 63-70.
[21]
Han J, Kamber M, Pei J.Data Mining Concepts and Techniques[M]. The 3rd Edition. New York: Morgan Kaufmann, 2012.
[22]
R语言LDA可视化包LDAvis[EB/OL]. [2018-02-28]..
[22]
(A LDA Visualization Package in R[EB/OL]. [2018-02-28]..)
(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.)
(Yi Lanli.Research on Statistical Characteristic Analysis and Modeling for User Behavior in Microblog Community Based on Human[D]. Beijing: Beijing University of Posts and Telecommunications, 2012.)
(Song Enmei, Zuo Huihui.Authority and Popularity: Social Network Analysis on Sina Microblogging[J]. Document, Information & Knowledge, 2012(3): 43-54.)
(Wang Xiaoguang.Empirical Analysis on Behavior Characteristics and Relation Characteristics of Micro-blog Users——Take “Sina Micro-blog” for Example[J]. Library and Information Service, 2010, 54(14): 66-70.)
[27]
Qu Y, Wu P F, Wang X.Online Community Response to Major Disaster: A Study of Tianya Forum in the 2008 Sichuan Earthquake[C]// Proceedings of the 42nd Hawaii International Conference on System Sciences. IEEE, 2009: 1-11.
