Navigating artificial intelligence narratives in Chinese media: a mixed-methods discourse analysis

主流 框架(结构) 叙述的 社会学 语篇分析 框架分析 叙述性探究 公司治理 意识形态 批评性话语分析 中国 语言学 民族主义 情报分析 认识论 机制(生物学) 政治学 新闻媒体 主观性 公共话语 认知 媒体研究 规范性
作者
Yuhang Li,Danni Yu,Lisai Yu
出处
期刊:Digital Scholarship in the Humanities [Oxford University Press]
卷期号:41 (2): 830-846
标识
DOI:10.1093/llc/fqag004
摘要

Abstract With the deepening social penetration of artificial intelligence (AI) technology, mainstream media’s role in shaping public cognition through news framing has become increasingly prominent. However, existing research has long been constrained by Western-centric perspectives, leaving significant gaps in exploring the discourse construction mechanism related to AI in non-Western contexts. This study seeks to systematically deconstruct the mainstream media narrative strategies on AI technology in the Chinese context, by employing a hybrid methodology combining Analysis of Topic Model Networks, Moral Foundation Analysis, and linguistic analysis and using AI-related news reports from 2017 to 2024 in Chinese mainstream media as a corpus. The findings suggest that, first, the media have constructed four frames of “Politics and Economy,” “Society,” “Revolution,” and “Cooperation,” whose structural details reflect the deep coupling between technological discourse and national strategies. Second, moral discourse demonstrates Chinese characteristics prioritizing dimensions of Authority/Subversion and Loyalty/Betrayal, whose diachronic growth correlates with contextual factors such as pandemic governance and nationalist reinforcement. Third, through the combined linguistic strategies of predication and metaphor, media narrate AI as a manipulable national development tool while downplaying technological complexity and threats. This study not only reveals the mutual-construction mechanism between ideology and discursive strategies in technological socialization, but also provides Chinese empirical references for global AI governance research through a non-Western perspective.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
Albert完成签到,获得积分10
2秒前
Hello应助从容的半青采纳,获得10
2秒前
顾思凡发布了新的文献求助10
5秒前
kyt完成签到,获得积分10
5秒前
完美兔子应助敏感板栗采纳,获得10
5秒前
123完成签到,获得积分10
5秒前
张欢馨应助LDX采纳,获得10
5秒前
江佳怡发布了新的文献求助10
6秒前
英姑应助故园无此声采纳,获得10
7秒前
8秒前
123发布了新的文献求助20
9秒前
喜悦井完成签到,获得积分10
9秒前
14秒前
14秒前
15秒前
竹噶发布了新的文献求助10
15秒前
科研通AI6.2应助dom采纳,获得10
17秒前
dm11完成签到,获得积分10
18秒前
19秒前
CX330发布了新的文献求助10
19秒前
19秒前
维维完成签到,获得积分20
20秒前
ken关闭了ken文献求助
20秒前
柒年发布了新的文献求助10
20秒前
慕青应助yichen采纳,获得10
21秒前
orixero应助等日落采纳,获得10
22秒前
woshi123应助江河采纳,获得10
22秒前
zzz小秦完成签到 ,获得积分10
22秒前
天天快乐应助看什么看采纳,获得10
23秒前
23秒前
23秒前
24秒前
脑洞疼应助亢kxh采纳,获得10
24秒前
脑洞疼应助陶醉的向南采纳,获得10
25秒前
辛勤青曼完成签到,获得积分10
28秒前
dxftx发布了新的文献求助10
29秒前
31秒前
科研通AI6.4应助柒年采纳,获得10
31秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7589261
求助须知:如何正确求助?哪些是违规求助? 9167150
关于积分的说明 19621037
捐赠科研通 7168988
什么是DOI,文献DOI怎么找? 3267113
关于科研通互助平台的介绍 2432050
邀请新用户注册赠送积分活动 2259271