Article(id=1282030044600046057, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.07.0181, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741622400000, receivedDateStr=2025-03-11, revisedDate=1747324800000, revisedDateStr=2025-05-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1783589381599, onlineDateStr=2026-07-09, pubDate=1753632000000, pubDateStr=2025-07-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783589381599, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783589381599, creator=13701087609, updateTime=1783589381599, updator=13701087609, issue=Issue{id=1282029960869167928, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='7', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='1753632000000', pubDateStr='2025-07-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783589361636, creator='13701087609', updateTime=1783589710614, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282031424651903975, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282031424656098280, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=218, endPage=224, ext={EN=ArticleExt(id=1282030044797178346, articleId=1282030044600046057, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Evaluation model of online emergency language effectiveness and its application based on persuasion theory, columnId=1149733268699918866, journalTitle=China Safety Science Journal, columnName=Emergency technology and management, runingTitle=null, highlight=null, articleAbstract=

To enhance the scientific nature and effectiveness of online emergency language services, based on Hovland's persuasion theory, it identified the factors influencing the effectiveness of online emergency language services, clarified the input and output indicators for evaluating emergency language services, constructed an evaluation system for the effectiveness of online emergency language services during the emergency response phase, and established an evaluation process for the effectiveness of emergency language services. Taking the 6·21 Yinchuan Barbecue Shop Explosion Accident as an example, big data analysis was conducted on the information released by official media on the Weibo platform during the emergency response phase. Five types of media accounts were identified as decision-making units (DMU): emergency (including firefighting) media, public prosecution and law enforcement media, central-level mainstream media, other government media, and local-level media. The date envelopment analysis(DEA) method was employed to evaluate the effectiveness of emergency language services. The results of this study illustrated that the effectiveness of online emergency language service is from high to low for the central-level mainstream media, public prosecution and law enforcement media, emergency (include firefighting) media, other government and local-level media. There is a significant gap between other government and local-level media and the top three types of media in terms of emergency language service effectiveness. Further exploration is needed to identify ways to improve the effectiveness of emergency language services for these media types.

, authors=Jianwu CHEN^{1, 2}, Jingqi GAO^{**, 2, 3}, Jingge XU¹, Qun LI³, Lewenyu PAN², Xiaofei ZHAO⁴, authorsList=Jianwu CHEN, Jingqi GAO, Jingge XU, Qun LI, Lewenyu PAN, Xiaofei ZHAO, authorCompany=null, correspAuthors=Jingqi GAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1282030045233385965, articleId=1282030044600046057, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于说服理论的在线应急语言有效性评价模型及其应用, columnId=1149733268855108116, journalTitle=中国安全科学学报, columnName=应急技术与管理, runingTitle=null, highlight=null, articleAbstract=

为提高在线应急语言服务的科学性和有效性，基于Hovland说服理论识别在线应急语言有效性的影响因素，明确应急语言服务评价投入指标和产出指标，构建应急响应阶段的在线应急语言服务有效性评价模型，并建立应急语言服务有效性评价流程；以宁夏银川富洋烧烤店“6·21”特别重大燃气爆炸事故为例，利用大数据分析应急响应阶段微博平台上官方媒体发布的信息，确定应急（含消防）类、公检法类、中央级主流媒体、其他政府类、地方级媒体账号5项类传播者主体并将其作为决策单元（DMU）；采用数据包络分析（DEA）方法开展应急语言服务有效性评价。研究结果表明：在线应急语言服务有效性从高到低为中央级主流媒体、公检法类媒体、应急（含消防）类媒体、其他政府类和地方级媒体，其他政府和地方级媒体与前3类传播主体还有较大差异，需要进一步探索其应急语言服务有效性提高的方式方法。

, authors=陈建武正高级工程师^{1, 2}, 高婧琦工程师^{**, 2, 3}, 徐晶格¹, 李群教授级高级工程师³, 潘乐文宇², 赵晓飞⁴, authorsList=陈建武正高级工程师, 高婧琦工程师, 徐晶格, 李群教授级高级工程师, 潘乐文宇, 赵晓飞, authorCompany=null, correspAuthors=高婧琦工程师, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=WBONKx2TEq1wA5VTlaoJ1g==, magXml=CccVY/nbMq/8TMzGDE2P4w==, pdfUrl=null, pdf=6FGgiEBKKlcKioOpyKvowA==, pdfFileSize=4014131, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=bBPWHq6FKt9ECg/sfrlcxg==, mapNumber=null, fund=null)}, authors=[Author(id=1282030045745091067, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282030044600046057, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=cjw3000@126.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282030045820588542, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282030044600046057, authorId=1282030045745091067, language=EN, stringName=Jianwu CHEN, firstName=Jianwu, middleName=null, lastName=CHEN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹Department of Human Resources and Talent, China Academy of Safety Science and Technology, Beijing 100012, China
²School of Engineering and Technology, China University of Geosciences (Beijing), Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282030045904474623, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282030044600046057, authorId=1282030045745091067, language=CN, stringName=陈建武正高级工程师, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹中国安全生产科学研究院 人事人才部，北京 100012
²中国地质大学（北京） 工程技术学院，北京 100083, bio={"content":"

陈建武（1981—），男，河北衡水人，博士，教授，主要从事职业安全健康与应急管理技术方面的研究。E-mail: cjw3000@126.com。

"}, bioImg=null, bioContent=

陈建武（1981—），男，河北衡水人，博士，教授，主要从事职业安全健康与应急管理技术方面的研究。E-mail: cjw3000@126.com。

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