Article(id=1288943065473856029, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1288943062634316606, articleNumber=null, orderNo=null, doi=10.19293/j.cnki.1673-8357.2026.01.001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1759161600000, receivedDateStr=2025-09-30, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1785237574213, onlineDateStr=2026-07-28, pubDate=1771516800000, pubDateStr=2026-02-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1785237574213, onlineIssueDateStr=2026-07-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1785237574213, creator=13701087609, updateTime=1785237574213, updator=13701087609, issue=Issue{id=1288943062634316606, tenantId=1146029695717560320, journalId=1149652312894775300, year='2026', volume='21', issue='1', pageStart='5', pageEnd='118', issueExtLink='null', onlineDate='null', pubDate='1771516800000', pubDateStr='2026-02-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1785237573536, creator='13701087609', updateTime=1785237687490, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1288943540701085861, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1288943062634316606, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1288943540701085862, tenantId=1146029695717560320, journalId=1149652312894775300, issueId=1288943062634316606, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=5, endPage=15, ext={EN=ArticleExt(id=1288943065650016798, articleId=1288943065473856029, tenantId=1146029695717560320, journalId=1149652312894775300, language=EN, title=Deep Synthesis Personas in Science Communication: A Content Analysis of Bilibili Videos, columnId=1288930244673511825, journalTitle=Studies on Science Popularization, columnName=Special, runingTitle=null, highlight=null, articleAbstract=

Can a technically synthesized persona function as a credible and effective communicator? Deep synthesis personas are showing distinctive potential in science communication, yet their inherently synthetic nature can trigger psychological resistance and raise doubts about message credibility. This study examines how shortening the psychological distance between audiences and deep synthesis personas can improve communication effects. We adopt the Elaboration Likelihood Model (ELM) as the primary framework and incorporate psychological distance theory to integrate the analysis. Using a sample of deep synthesis persona science videos from Bilibili (N=193), we combined web scraping with manual coding and estimated regression models to test how features related to content and technology shaping effects, including reach, engagement, and endorsement. The results show that, on the content route, multi-character interactive discussion formats, as compared with solo monologue formats, and narration delivered through reanimated authentic historical figures, as compared with fictional characters, effectively reduce psychological distance and foster a more active discussion climate. On the technology route, higher visual realism and smoother, more natural facial animation increase viewers’ sense of presence and perceived authenticity, shorten psychological distance from the persona, and in turn raise interactive behaviors and positive feedback. In parallel, peripheral cues such as creator prominence exert significant positive effects on diffusion metrics, underscoring the importance of source credibility. These findings offer practical guidance for video production and dissemination strategy and provide a theoretical reference for understanding the opportunities and social implications of deploying deep synthesis technologies in science communication.

, authors=Yi Xiao, Jiangtong Li, Minyao Zhang, authorsList=Yi Xiao, Jiangtong Li, Minyao Zhang, authorCompany=null, correspAuthors=Jiangtong Li, 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=1288943065872314911, articleId=1288943065473856029, tenantId=1146029695717560320, journalId=1149652312894775300, language=CN, title=深度合成人物形象科普视频的传播效果与影响因素研究——基于B站视频的内容分析, columnId=1288943042333880741, journalTitle=科普研究, columnName=专题, runingTitle=null, highlight=null, articleAbstract=

运用深度合成技术塑造的人物形象能否成为一个可信的科普传播者？深度合成的人物形象在科普中展现出独特的传播潜力，然而，由于此类内容天然带有技术伪造属性，容易导致用户对深度合成人物形象所传达的科普内容产生心理抵触，从而质疑内容的可信度。本研究聚焦“深度合成人物形象用于科普”这一主题，探讨如何通过缩短用户与深度合成人物形象之间的心理距离来提升科普效果，并以详尽可能性模型（ELM）为理论视角，引入心理距离理论加以综合分析。本研究对B站中应用深度合成人物形象进行科普的视频样本（N=193）进行人工编码，通过回归模型检验该类科普视频的内容特征和技术特征对传播广度、传播参与度和传播认同度等效果指标的影响。结果表明：多个深度合成人物之间的互动讨论式叙事呈现（vs.个人独白）与复活真实人物形象（vs.虚拟人物形象）进行科普的形式可有效降低用户心理距离、引发更积极的讨论；深度合成人物形象的形象逼真程度和表情自然度越高越能提升用户的社会临场感和真实感知，缩短用户与深度合成人物的心理距离，进而提高视频的互动量和正向反馈；此外，视频发布者的知名度等边缘路径线索对传播效果也有显著正向作用，体现了信息来源可信度在传播中的重要性。本研究旨在为视频创作和视频传播策略优化提供实践性的启示，并为理解AI深度合成技术在科普中的应用潜力与社会影响提供理论参考。

, authors=肖毅, 李江彤, 张旻尧, authorsList=肖毅, 李江彤, 张旻尧, authorCompany=null, correspAuthors=李江彤, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=XR9SzZWyRA2KjcRa9VYXUQ==, magXml=IxH4xQErwloj8dSQ6tJ6MA==, pdfUrl=null, pdf=FOtfNKtdNBa79/ZKdQWlRA==, pdfFileSize=2315111, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=W4OcYXu/+jqe2NY0W2Xa/A==, mapNumber=null, fund=null)}, authors=[Author(id=1288943066144944676, tenantId=1146029695717560320, journalId=1149652312894775300, articleId=1288943065473856029, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=yixiao@tju.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1288943066220442150, tenantId=1146029695717560320, journalId=1149652312894775300, articleId=1288943065473856029, authorId=1288943066144944676, language=EN, stringName=Yi Xiao, firstName=Yi, middleName=null, lastName=Xiao, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of New Media and Communication, Tianjin University, Tianjin 300072, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1288943066308522535, tenantId=1146029695717560320, journalId=1149652312894775300, articleId=1288943065473856029, authorId=1288943066144944676, language=CN, stringName=肖毅, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=天津大学新媒体与传播学院，天津　300072, bio={"content":"

肖毅，天津大学新媒体与传播学院副教授，研究方向：科学传播、人机传播，E-mail：yixiao@tju.edu.cn。

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肖毅，天津大学新媒体与传播学院副教授，研究方向：科学传播、人机传播，E-mail：yixiao@tju.edu.cn。

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