Article(id=1289658568299356789, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1289658413093335532, articleNumber=null, orderNo=null, doi=10.19293/j.cnki.1673-8357.2016.04.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1453737600000, receivedDateStr=2016-01-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1785408163380, onlineDateStr=2026-07-30, pubDate=1470758400000, pubDateStr=2016-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1785408163380, onlineIssueDateStr=2026-07-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1785408163380, creator=13701087609, updateTime=1785408163380, updator=13701087609, issue=Issue{id=1289658413093335532, tenantId=1146029695717560320, journalId=1149652312894775300, year='2016', volume='11', issue='4', pageStart='5', pageEnd='93', issueExtLink='null', onlineDate='null', pubDate='1470758400000', pubDateStr='2016-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1785408126376, creator='13701087609', updateTime=1785408482500, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1289659906815017653, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1289658413093335532, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1289659906815017654, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1289658413093335532, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=27, endPage=34, ext={EN=ArticleExt(id=1289658569473761911, articleId=1289658568299356789, tenantId=1146029695717560320, journalId=1149652312894775300, language=EN, title=A Study on the Media Monitoring Approach for Science Communication, columnId=1288940546366484611, journalTitle=Studies on Science Popularization, columnName=Theoretical Studies, runingTitle=null, highlight=null, articleAbstract=

Media monitoring approach focusing on scientific texts can provide a reflection on the texture of public science and reveal the different roles assumed by the media and other social groups during the communication of science. Texture analysis on media discourses is thus useful to achieve the above-mentioned goals, especially when assisted with analytical techniques of text coding and feature reduction based on procedures such as thematic indexing and keyword screening. In the paper, we made texture analysis on an amount of scientific coverage that appeared in two different newspapers, namely, People’s Daily and Southern Weekly, it not only draws an overall picture of how various science issues compete against each other in the news, but also leads the way to the construction of scientific corpora and keyword lexicon which in turn lay a theoretical and utilizable foundation of a more comprehensive monitoring approach to the process of informational dissemination of public science.

, authors=Liming Wang^*, Qi Zhong, authorsList=Liming Wang, Qi Zhong, authorCompany=null, correspAuthors=Liming Wang, 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=1289658572392997497, articleId=1289658568299356789, tenantId=1146029695717560320, journalId=1149652312894775300, language=CN, title=面向科学传播的媒体监测方法研究, columnId=1288940546622341443, journalTitle=科普研究, columnName=理论探索, runingTitle=null, highlight=null, articleAbstract=

聚焦科技文本的媒体监测可以反映出媒体上的公众科学的基本结构，并揭示出大众媒体及其他社会群体在科学传播中的作用和影响。围绕这些媒体监测目标，可将针对科技文本的结构分析作为实现途径，其中基于主题索引和特征词筛选的文本编码和特征降维是主要的技术手段。基于对《人民日报》和《南方周末》部分科学传播文本的结构分析，笔者对国内大众媒体上的科学议题分布取得了基本理解，并建构了一套初步的科学传播语料库和特征词库，为后期全面开展科普信息化监测奠定了理论和工具基础。

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