Article(id=1317436248147476889, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1317436203545243877, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1744214400000, receivedDateStr=2025-04-10, revisedDate=1751558400000, revisedDateStr=2025-07-04, acceptedDate=null, acceptedDateStr=null, onlineDate=1792030878340, onlineDateStr=2026-10-15, pubDate=1786723200000, pubDateStr=2026-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792030878340, onlineIssueDateStr=2026-10-15, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792030878340, creator=13701087609, updateTime=1792030878340, updator=13701087609, issue=Issue{id=1317436203545243877, tenantId=1146029695717560320, journalId=1308397381743640680, year='2026', volume='44', issue='8', pageStart='1569', pageEnd='1792', issueExtLink='null', onlineDate='null', pubDate='1786723200000', pubDateStr='2026-08-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792030867705, creator='13701087609', updateTime=1792031039088, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1317436922423792157, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1317436203545243877, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1317436922427986462, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1317436203545243877, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1647, endPage=1657, ext={EN=ArticleExt(id=1317436248340414874, articleId=1317436248147476889, tenantId=1146029695717560320, journalId=1308397381743640680, language=EN, title=Information exposure and threat situation: An exploratory analysis of the causes of public cognitive polarization, columnId=1309226307540574209, journalTitle=Studies in Science of Science, columnName=Theories and Methods, runingTitle=null, highlight=null, articleAbstract=
The rapid development of intelligent technologies is propelling humanity toward an intelligent society, bringing about profound changes in production, lifestyle, organizational structures, and social order. These transformations have given rise to numerous new challenges, making the governance of intelligent society an urgent research agenda. While existing studies have addressed key risks associated with intelligent technologies—including algorithmic abuse, the digital divide, and issues of trust and fatigue—relatively less attention has been paid to the transformative impact of intelligent recommendation systems on public information exposure, cognitive patterns, and behavioral preferences. The widespread use of personalized recommendations often results in individuals being repeatedly exposed to homogeneous content, leading to the formation of information cocoons, exacerbating cognitive polarization, and increasing the risk of societal fragmentation. This presents a significant challenge for intelligent social governance.
Traditional analyses of public cognition and attitude formation are often based on the rational actor model, assuming that individuals make decisions through cost-benefit calculations. However, such perspectives tend to overlook the psychological and emotional mechanisms involved in information processing. Recent studies from the fields of psychology and behavioral science have begun to explore how emotional preferences, identity, ideology, and personality traits influence the relationship between information exposure and cognitive polarization. Nevertheless, little attention has been given to the role of perceived external social environments, especially perceptions of societal threats. Psychological research indicates that perceived threats in the social environment significantly shape individual cognition and attitudes. In today’s digital landscape, where intelligent technologies dominate, threat-inducing and emotionally charged content is more likely to attract attention and be widely disseminated. This can amplify public anxiety and perceptions of insecurity, thereby intensifying cognitive polarization. Accordingly, this study seeks to bridge the gap by examining how threat perceptions and information exposure interact to influence public cognitive polarization.
This paper introduces the perspective of external threat situations and explores how they, together with information exposure, jointly influence public cognitive polarization. Using the application of facial recognition technology in “pedestrian red-light violation exposure” as a case study, this research constructs a 2 (no threat situation vs. threat situation)×2 (homogeneous information vs. heterogeneous information) between-subjects experiment. A total of 1,281 participants were recruited online for the experiment. The results indicate that exposure to homogeneous information strengthens the public’s original views, thereby intensifying cognitive polarization, while exposure to heterogeneous information weakens the public’s original views, reducing cognitive polarization. Compared to the absence of external threat situations, threat situations significantly weaken the depolarization effect brought about by exposure to heterogeneous information. Additionally, for individuals of different genders and average annual incomes, threat situations play varying roles in the process by which information exposure influences polarization.
The findings demonstrate that the external environment in which the public is situated, including threat perceptions caused by social unrest, economic crises, crime, disease risks, and unexpected events, may have a significant impact on changes in cognitive polarization during information exposure. This deserves further attention and research. Moreover, when the government addresses viewpoint polarization in cyberspace, it should not only promote the public’s exposure to more heterogeneous information that challenges their original views and encourages diverse thinking, but also pay attention to the external environment the public faces. This can help reduce public anxiety and threat perception, thereby enhancing the role of heterogeneous information in mitigating viewpoint polarization.
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伴随社会智能化转型,精准推荐等新技术引发的认知极化问题日益成为社会治理的重要议题。研究基于行为科学视角,探讨社会环境中的威胁情境如何与智能精准推荐下的信息接触产生交互作用,影响公众认知极化进程。通过设计2(无威胁情境VS威胁情境)×2(同质信息VS异质信息)的双因素被试间实验,研究发现接触同质信息会加剧公众认知极化,而接触异质信息则有助于缓解极化;存在威胁情境时,接触异质信息对公众认知极化的缓解作用会减弱。结果表明,对智能社会中公众认知极化问题的治理,不仅要破除精准推荐带来的信息茧房,还需重视社会环境中的威胁情境对公众认知的影响。
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40(10): 118-132., articleTitle=Risk perception of the public and acceptance of emerging technologies: A survey experiment on facial recognition technology, refAbstract=null)], funds=[Fund(id=1317436262395527646, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, awardId=2022YFC3303100, language=CN, fundingSource=国家重点研发计划项目(2022YFC3303100), fundOrder=null, country=null), Fund(id=1317436262458442207, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, awardId=72104126, language=CN, fundingSource=国家自然科学基金资助项目(72104126), fundOrder=null, country=null), Fund(id=1317436262521356768, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, awardId=72204138, language=CN, fundingSource=国家自然科学基金资助项目(72204138), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1317436249682592166, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, xref=null, ext=[AuthorCompanyExt(id=1317436249690980775, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, companyId=1317436249682592166, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Policy and Management, Tsinghua University, Beijing 100086, China), AuthorCompanyExt(id=1317436249699369384, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, companyId=1317436249682592166, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=清华大学公共管理学院, 北京 100086)])], figs=[ArticleFig(id=1317436258205417927, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Figure 1, caption=
Experimental procedure flowchart, figureFileSmall=kVSsrJyEiXDaDcmn4qU41Q==, figureFileBig=Ute/YiSnPkIbatpFaFKvEA==, tableContent=null), ArticleFig(id=1317436258545156552, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=图1, caption=
实验流程示意图, figureFileSmall=kVSsrJyEiXDaDcmn4qU41Q==, figureFileBig=Ute/YiSnPkIbatpFaFKvEA==, tableContent=null), ArticleFig(id=1317436259061055946, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Figure 2, caption=
Video materials presented to the threat and no-threat groups, figureFileSmall=VreQO4K/2Kopu85x2w00nA==, figureFileBig=1+/f6pWlKKKaNxzlxl8J6Q==, tableContent=null), ArticleFig(id=1317436260713611723, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=图2, caption=
有威胁组、无威胁组使用的视频材料, figureFileSmall=VreQO4K/2Kopu85x2w00nA==, figureFileBig=1+/f6pWlKKKaNxzlxl8J6Q==, tableContent=null), ArticleFig(id=1317436260810080716, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Figure 3, caption=
The effect of information exposure on opinion polarization, figureFileSmall=vk16lrc2mUg0JXYPROoz3g==, figureFileBig=1N0Nt+5SoHoFPFybiekVEQ==, tableContent=null), ArticleFig(id=1317436261053350349, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=图3, caption=
信息接触对观点极端程度的影响, figureFileSmall=vk16lrc2mUg0JXYPROoz3g==, figureFileBig=1N0Nt+5SoHoFPFybiekVEQ==, tableContent=null), ArticleFig(id=1317436261128847822, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Figure 4, caption=
Frequency distribution of opinion polarization before and after information exposure across groups, figureFileSmall=Hc55U1mUq8FSuEq0P3xicA==, figureFileBig=tfjzSHDa2zxFT0aipMMmiQ==, tableContent=null), ArticleFig(id=1317436261204345295, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=图4, caption=
不同分组接触信息前后观点极端程度频率分布, figureFileSmall=Hc55U1mUq8FSuEq0P3xicA==, figureFileBig=tfjzSHDa2zxFT0aipMMmiQ==, tableContent=null), ArticleFig(id=1317436261284037072, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Figure 5, caption=
Changes in opinion polarization across threat contexts and types of information exposure, figureFileSmall=DwUrlnZC51OgVaYHZmmEkA==, figureFileBig=U+nHUQ74HCjRZcY9sZ5w4A==, tableContent=null), ArticleFig(id=1317436261355340241, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=图5, caption=
不同威胁情境与信息接触下观点极端改变程度, figureFileSmall=DwUrlnZC51OgVaYHZmmEkA==, figureFileBig=U+nHUQ74HCjRZcY9sZ5w4A==, tableContent=null), ArticleFig(id=1317436261439226322, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 1, caption=
Experimental conditions and grouping
, figureFileSmall=null, figureFileBig=null, tableContent=
| 实验组1 | 实验组2 | 实验组3 | 实验组4 |
| 威胁情境 | 无威胁 | 无威胁 | 有威胁 | 有威胁 |
| 信息接触类型 | 同质信息 | 异质信息 | 同质信息 | 异质信息 |
| 样本数 | 327 | 316 | 314 | 324 |
), ArticleFig(id=1317436261523112403, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表1, caption=
实验条件与分组
, figureFileSmall=null, figureFileBig=null, tableContent=
| 实验组1 | 实验组2 | 实验组3 | 实验组4 |
| 威胁情境 | 无威胁 | 无威胁 | 有威胁 | 有威胁 |
| 信息接触类型 | 同质信息 | 异质信息 | 同质信息 | 异质信息 |
| 样本数 | 327 | 316 | 314 | 324 |
), ArticleFig(id=1317436261590221268, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 2, caption=
Descriptive analysis results of major demographic variables
, figureFileSmall=null, figureFileBig=null, tableContent=
| 人口统计学变量(定类) | 频数 | 百分比 |
| 性别 | 男 | 618 | 48.20% |
| 女 | 663 | 51.80% |
| 职业 | 政府单位 | 38 | 3% |
| 事业单位 | 94 | 7.30% |
| 国企 | 147 | 11.50% |
| 私企 | 643 | 50.20% |
| 教育科研单位 | 14 | 1.10% |
| 学生 | 298 | 23.30% |
| 无业/失业 | 8 | 0.60% |
| 其他 | 39 | 3.00% |
| 最高学历 | 小学及以下 | 0 | 0% |
| 初中 | 6 | 0.50% |
| 普高/中专/技校/职高 | 47 | 4.10% |
| 专科 | 123 | 13.70% |
| 本科 | 903 | 70.50% |
| 硕士 | 190 | 14.80% |
| 博士 | 12 | 0.90% |
| 年收入水平 | 0-5000元 | 107 | 8.40% |
| 5000-1万元 | 79 | 6.20% |
| 1万-3万元 | 100 | 7.80% |
| 3万-5万元 | 75 | 5.90% |
| 5万-10万元 | 254 | 19.80% |
| 10万-20万元 | 394 | 30.80% |
| 20万-50万元 | 224 | 17.50% |
| 50万-100万元 | 44 | 3.40% |
| 100万元及以上 | 4 | 0.30% |
| 人口统计学变量(定量) | 均值 | 标准差 | |
| 年龄 | 整数年龄 | 30.878 | 10.496 |
| 主观社会阶层 | 1=最底层,10=最顶层 | 5.263 | 1.516 |
), ArticleFig(id=1317436261665718741, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表2, caption=
主要人口统计学变量描述性分析结果
, figureFileSmall=null, figureFileBig=null, tableContent=
| 人口统计学变量(定类) | 频数 | 百分比 |
| 性别 | 男 | 618 | 48.20% |
| 女 | 663 | 51.80% |
| 职业 | 政府单位 | 38 | 3% |
| 事业单位 | 94 | 7.30% |
| 国企 | 147 | 11.50% |
| 私企 | 643 | 50.20% |
| 教育科研单位 | 14 | 1.10% |
| 学生 | 298 | 23.30% |
| 无业/失业 | 8 | 0.60% |
| 其他 | 39 | 3.00% |
| 最高学历 | 小学及以下 | 0 | 0% |
| 初中 | 6 | 0.50% |
| 普高/中专/技校/职高 | 47 | 4.10% |
| 专科 | 123 | 13.70% |
| 本科 | 903 | 70.50% |
| 硕士 | 190 | 14.80% |
| 博士 | 12 | 0.90% |
| 年收入水平 | 0-5000元 | 107 | 8.40% |
| 5000-1万元 | 79 | 6.20% |
| 1万-3万元 | 100 | 7.80% |
| 3万-5万元 | 75 | 5.90% |
| 5万-10万元 | 254 | 19.80% |
| 10万-20万元 | 394 | 30.80% |
| 20万-50万元 | 224 | 17.50% |
| 50万-100万元 | 44 | 3.40% |
| 100万元及以上 | 4 | 0.30% |
| 人口统计学变量(定量) | 均值 | 标准差 | |
| 年龄 | 整数年龄 | 30.878 | 10.496 |
| 主观社会阶层 | 1=最底层,10=最顶层 | 5.263 | 1.516 |
), ArticleFig(id=1317436261728633302, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 3, caption=
Test for baseline balance
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量均值 | 实验组1 | 实验组2 | 实验组3 | 实验组4 | F / Chi2 | P |
| 性别 | 0.47 | 0.47 | 0.48 | 0.5 | 0.3 | 0.826 |
| 年龄 | 30.4 | 30.78 | 31.31 | 31.03 | 0.434 | 0.729 |
| 受教育水平(最低年限) | 16.15 | 16.35 | 16.21 | 16.19 | 1.008 | 0.389 |
| 年收入 | 145672.78 | 149050.63 | 164148.09 | 163989.2 | 1.097 | 0.349 |
| 主观社会阶层 | 5.17 | 5.35 | 5.19 | 5.35 | 1.362 | 0.253 |
| 职业 | - | - | - | - | 15.0 | 0.823 |
), ArticleFig(id=1317436261808325079, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表3, caption=
平衡性检验
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量均值 | 实验组1 | 实验组2 | 实验组3 | 实验组4 | F / Chi2 | P |
| 性别 | 0.47 | 0.47 | 0.48 | 0.5 | 0.3 | 0.826 |
| 年龄 | 30.4 | 30.78 | 31.31 | 31.03 | 0.434 | 0.729 |
| 受教育水平(最低年限) | 16.15 | 16.35 | 16.21 | 16.19 | 1.008 | 0.389 |
| 年收入 | 145672.78 | 149050.63 | 164148.09 | 163989.2 | 1.097 | 0.349 |
| 主观社会阶层 | 5.17 | 5.35 | 5.19 | 5.35 | 1.362 | 0.253 |
| 职业 | - | - | - | - | 15.0 | 0.823 |
), ArticleFig(id=1317436261908988376, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 4, caption=
Content of the information exposure materials
, figureFileSmall=null, figureFileBig=null, tableContent=
| 支持类 | A1:那些闯红灯的人就是图方便,把自己的生命安全,别人的生命安全都不当回事。交警又没空天天蹲路口抓闯红灯的人,这种人早该被好好教育教育了!我看曝光人脸,让他们丢丢脸,是当前最实用的方法。 |
| A2:交通法中对于交通信号灯的规则有明确规定,红灯停绿灯行是法定规则,遵纪守法是公民基本要求。本来就应该根据交通法规走路行车,这个系统在降低闯红灯行为频率上效果确实不错。违法行为被公检系统发现并曝光,蛮正常的。想避免丢脸就改正,法律是用来规范人的行为的。 |
| A3:支持!我家这边闯红灯的人特别多,正需要这种系统好好警示一下!听说身边安装了这个设备的路口确实闯红灯的人变少了,公开个人信息确实比较社死,但这样才能有效教育这些不守交规的人呀! |
| 反对类 | B1:虽然这个方法确实有用,但是把个人的脸放上去循环公示过分了吧。教育个人遵守交规还有很多手段,比如定位到个人,短信通知或者罚款,没必要让人“社死”。这样公示人家的脸根本没考虑会对这个人有什么恶劣影响啊。 |
| B2:罚款可以,但是在大街上公示人脸抓拍,是不是太侵犯隐私了......毕竟闯红灯的行人个体对公共安全的伤害还是很小的,那些危害性更大的闯红灯的大车也只是罚款而已,凭什么单单要把一个闯红灯拿出来曝光给大庭广众呢? |
| B3:也就是闯个红灯,这样的惩罚有必要吗?人脸和个人信息是公民的隐私,怎么还有交警把闯红灯的人的信息记录下来发到网上接着曝光啊?在当地大屏曝光还不够是吗? |
), ArticleFig(id=1317436261980291545, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表4, caption=
信息接触材料的内容
, figureFileSmall=null, figureFileBig=null, tableContent=
| 支持类 | A1:那些闯红灯的人就是图方便,把自己的生命安全,别人的生命安全都不当回事。交警又没空天天蹲路口抓闯红灯的人,这种人早该被好好教育教育了!我看曝光人脸,让他们丢丢脸,是当前最实用的方法。 |
| A2:交通法中对于交通信号灯的规则有明确规定,红灯停绿灯行是法定规则,遵纪守法是公民基本要求。本来就应该根据交通法规走路行车,这个系统在降低闯红灯行为频率上效果确实不错。违法行为被公检系统发现并曝光,蛮正常的。想避免丢脸就改正,法律是用来规范人的行为的。 |
| A3:支持!我家这边闯红灯的人特别多,正需要这种系统好好警示一下!听说身边安装了这个设备的路口确实闯红灯的人变少了,公开个人信息确实比较社死,但这样才能有效教育这些不守交规的人呀! |
| 反对类 | B1:虽然这个方法确实有用,但是把个人的脸放上去循环公示过分了吧。教育个人遵守交规还有很多手段,比如定位到个人,短信通知或者罚款,没必要让人“社死”。这样公示人家的脸根本没考虑会对这个人有什么恶劣影响啊。 |
| B2:罚款可以,但是在大街上公示人脸抓拍,是不是太侵犯隐私了......毕竟闯红灯的行人个体对公共安全的伤害还是很小的,那些危害性更大的闯红灯的大车也只是罚款而已,凭什么单单要把一个闯红灯拿出来曝光给大庭广众呢? |
| B3:也就是闯个红灯,这样的惩罚有必要吗?人脸和个人信息是公民的隐私,怎么还有交警把闯红灯的人的信息记录下来发到网上接着曝光啊?在当地大屏曝光还不够是吗? |
), ArticleFig(id=1317436262068371930, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 5, caption=
Descriptive analysis results of key variables
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量名称 | 测量方式 | 样本量 | 均值 | 标准差 | 最大值 | 最小值 |
| 信息接触前观点极端程度 | 信息接触前的观点态度取值减去中立值(4.5)的绝对值 | 1281 | 2.254 | 0.96 | 3.5 | 0.5 |
| 信息接触后观点极端程度 | 信息接触后的观点态度取值减去中立值(4.5)的绝对值 | 1281 | 2.132 | 1.029 | 3.5 | 0.5 |
| 信息接触 | 1=同质信息;0=异质信息 | 1281 | 0.5 | 0.5 | 1.0 | 0.0_ |
| 威胁情境 | 1=有威胁;0=无威胁 | 1281 | 0.498 | 0.5 | 1.0 | 0.0 |
), ArticleFig(id=1317436262152258011, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表5, caption=
主要变量描述性分析结果
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| 变量名称 | 测量方式 | 样本量 | 均值 | 标准差 | 最大值 | 最小值 |
| 信息接触前观点极端程度 | 信息接触前的观点态度取值减去中立值(4.5)的绝对值 | 1281 | 2.254 | 0.96 | 3.5 | 0.5 |
| 信息接触后观点极端程度 | 信息接触后的观点态度取值减去中立值(4.5)的绝对值 | 1281 | 2.132 | 1.029 | 3.5 | 0.5 |
| 信息接触 | 1=同质信息;0=异质信息 | 1281 | 0.5 | 0.5 | 1.0 | 0.0_ |
| 威胁情境 | 1=有威胁;0=无威胁 | 1281 | 0.498 | 0.5 | 1.0 | 0.0 |
), ArticleFig(id=1317436262219366876, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=EN, label=Table 6, caption=
Interaction effect of threat condition and type of information exposure on change in opinion polarization
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量:观点极端改变程度 | 模型1:OLS回归 | 模型2:Logit回归 | 模型3:Probit回归 |
| coeff | LLCI | ULCI | coeff | LLCI | ULCI | coeff | LLCI | UI |
| 威胁情境(0=无威胁,1=有威胁) | 0.265*** | 0.133 | 0.397 | 1.039** | 0.424 | 1.654 | 0.512** | 0.217 | 0.8107 |
| 信息接触(1=同质,0=异质) | 1.071*** | 0.939 | 1.202 | 2.519** | 1.955 | 3.084 | 1.370*** | 1.096 | 1.645 |
| 威胁情境*信息接触 | -0.229* | -0.415 | -0.043 | -0.920** | -1.611 | -0.228 | -0.438* | -0.792 | -0.084 |
| 常数项 | -0.734*** | -0.828 | -0.640 | -2.999*** | -3.518 | -2.481 | -1.670*** | -1.907 | -1.433 |
| N | 1281 | 1281 | 1281 | | | | | | |
| R2/ Presudo R2 | 0.248 | 0.136 | 0.136 | | | | | | |
| Adjust-R2/ LLR p | 0.246 | <.001 | <.001 | | | | | | |
), ArticleFig(id=1317436262299058653, tenantId=1146029695717560320, journalId=1308397381743640680, articleId=1317436248147476889, language=CN, label=表6, caption=
威胁情境与信息接触类型对观点极化改变程度的交互作用
, figureFileSmall=null, figureFileBig=null, tableContent=
| 变量:观点极端改变程度 | 模型1:OLS回归 | 模型2:Logit回归 | 模型3:Probit回归 |
| coeff | LLCI | ULCI | coeff | LLCI | ULCI | coeff | LLCI | UI |
| 威胁情境(0=无威胁,1=有威胁) | 0.265*** | 0.133 | 0.397 | 1.039** | 0.424 | 1.654 | 0.512** | 0.217 | 0.8107 |
| 信息接触(1=同质,0=异质) | 1.071*** | 0.939 | 1.202 | 2.519** | 1.955 | 3.084 | 1.370*** | 1.096 | 1.645 |
| 威胁情境*信息接触 | -0.229* | -0.415 | -0.043 | -0.920** | -1.611 | -0.228 | -0.438* | -0.792 | -0.084 |
| 常数项 | -0.734*** | -0.828 | -0.640 | -2.999*** | -3.518 | -2.481 | -1.670*** | -1.907 | -1.433 |
| N | 1281 | 1281 | 1281 | | | | | | |
| R2/ Presudo R2 | 0.248 | 0.136 | 0.136 | | | | | | |
| Adjust-R2/ LLR p | 0.246 | <.001 | <.001 | | | | | | |
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