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Title:Predicting the influence of microblog entries regarding public health emergencies
Author(s):An, Lu; Yi, Xingyue; Yu, Chuanming; Li, Gang
Subject(s):Public health emergencies
Influence of microblog entries
Prediction
Random forest
BM25 Latent Dirichlet Allocation model (LDA-BM25)
Abstract:Predicting the influence of microblog entries regarding public health emergencies can help management departments improve the prospectiveness of decision making. In this study, we measure the influence of microblog entries regarding public health emergencies from their forwarding, comment and favorite counts. A microblog influence prediction model, which is comprised of user, time and content features, is proposed by using the random forest method and the BM25 Latent Dirichlet Allocation model (LDA-BM25). Microblog entries on the Ebola outbreak are selected as test data. Results reveal that the proposed model can accurately predict the influence of microblog entries regarding public health emergencies with the accuracy rate reaching 88.8%. Individual features, which play a role in the influence of microblog entries, and their influence inclination are also analyzed. The findings of the study can help management departments of public health emergencies predict the upcoming salient issues, and take appropriate measures in advance.
Issue Date:2017
Publisher:iSchools
Citation Info:An, L., Yi, X., Yu, C., & Li, G. (2017). Predicting the Influence of Microblog Entries Regarding Public Health Emergencies. In iConference 2017 Proceedings (pp. 79–94). https://doi.org/10.9776/17012
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper/Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/96686
DOI:https://doi.org/10.9776/17012
Rights Information:Copyright 2017 Lu An, Xingyue Yi, Chuanming Yu, and Gang Li
Date Available in IDEALS:2017-07-27


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