AI冲击何以引发职业焦虑？

——基于微博用户话语的失业风险感知研究

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Abstract：To investigateunemployment risk perception intheeraofartificial intelligence，thisstudyemployed sentiment analysis，LDAtopic modeling，and semantic network analysis todisect discourse from Weibo users between November30，2022，andDecember31，2024.Thefindingsreveal that：Sentiment withinuserdiscoursewaspredominantly negative，andthesynchronizationofinformationdiseminationandemotionalexpressioncontributedtothepolarizationof public opinion; User discourse coalesced around three categoriesofunemployment risk perception-“individual”， “occupational”and“societal"—respectively pointing tocrises of personal competency，occupational groupreplacement， andlarge-scale societalunemployment;The discoursereflected underlyingconflictsstemming frommaldistribution of social power，highlighting the tension between technological advancement and the safeguarding of social rights and benefits.

Keywords：unemployment risk perception; LDA topic modeling; semantic network analysis; discourse analysis

在第四次工业革命的技术转型中，人工智能技术的突破性发展驱动着社会系统发生重构。（剩余12798字）