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Leveraging cross-media analytics to detect events and mine opinions for emergency management
Xu, Wei1; Liu, Lingyu1; Shang, Wei2
2017
Source PublicationONLINE INFORMATION REVIEW
ISSN1468-4527
Volume41Issue:4Pages:487-506
AbstractPurpose - Timely detection of emergency events and effective tracking of corresponding public opinions are critical in emergency management. As media are immediate sources of information on emergencies, the purpose of this paper is to propose cross-media analytics to detect and track emergency events and provide decision support for government and emergency management departments. Design/methodology/approach - In this paper, a novel emergency event detection and opinion mining method is proposed for emergency management using cross-media analytics. In the proposed approach, an event detection module is constructed to discover emergency events based on cross-media analytics, and after the detected event is confirmed as an emergency event, an opinion mining module is used to analyze public sentiments and then generate public sentiment time series for early warning via a semantic expansion technique. Findings - Empirical results indicate that a specific emergency can be detected and that public opinion can be tracked effectively and efficiently using cross-media analytics. In addition, the proposed system can be used for decision support and real-time response for government and emergency management departments. Research limitations/implications - This paper takes full advantage of cross-media information and proposes novel emergency event detection and opinion mining methods for emergency management using cross-media analytics. The empirical analysis results illustrate the efficiency of the proposed method. Practical implications - The proposed method can be applied for detection of emergency events and tracking of public opinions for emergency decision support and governmental real-time response. Originality/value - This research work contributes to the design of a decision support system for emergency event detection and opinion mining. In the proposed approaches, emergency events are detected by leveraging cross-media analytics, and public sentiments are measured using an auto-expansion of the domain dictionary in the field of emergency management to eliminate the misclassification of the general dictionary and to make the quantization more accurate.
KeywordOpinion mining Cross-media analytics Emergence management Event detection Semantic expansion
DOI10.1108/OIR-08-2015-0286
Language英语
Funding ProjectNational Natural Science Foundation of China[71301163] ; National Natural Science Foundation of China[71571180] ; Humanities and Social Sciences Foundation of Ministry of Education[14YJA630075] ; Humanities and Social Sciences Foundation of Ministry of Education[15YJA630068] ; Hebei Social Science Fund[HB13GL021] ; Fundamental Research Funds for Central Universities ; Renmin University of China[10XNK159] ; Renmin University of China[15XNLQ08]
WOS Research AreaComputer Science ; Information Science & Library Science
WOS SubjectComputer Science, Information Systems ; Information Science & Library Science
WOS IDWOS:000407682900004
PublisherEMERALD GROUP PUBLISHING LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/26242
Collection系统科学研究所
Corresponding AuthorShang, Wei
Affiliation1.Renmin Univ China, Beijing, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Xu, Wei,Liu, Lingyu,Shang, Wei. Leveraging cross-media analytics to detect events and mine opinions for emergency management[J]. ONLINE INFORMATION REVIEW,2017,41(4):487-506.
APA Xu, Wei,Liu, Lingyu,&Shang, Wei.(2017).Leveraging cross-media analytics to detect events and mine opinions for emergency management.ONLINE INFORMATION REVIEW,41(4),487-506.
MLA Xu, Wei,et al."Leveraging cross-media analytics to detect events and mine opinions for emergency management".ONLINE INFORMATION REVIEW 41.4(2017):487-506.
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