This paper establishes an empirical baseline of public sentiment toward Fourth Industrial Revolution (4IR) technologies across six European countries during the period 2006--2019, prior to the widespread adoption of generative AI systems. Employing transformer-based natural language processing models on a corpus of approximately 90,000 tweets and news articles, I document a European public sphere increasingly divided in its assessment of technological change: neutral sentiment declined markedly over the study period as citizens sorted into camps of enthusiasm and concern, a pattern that manifests distinctively across national contexts and technology domains. Approximately 6\% of users inhabit echo chambers characterized by sentiment-aligned networks, with privacy discourse exhibiting the highest susceptibility to such dynamics. These findings provide a methodologically rigorous reference point for evaluating how the introduction of ChatGPT and subsequent generative AI systems has transformed public discourse on automation, employment, and technological change. The results carry implications for policymakers seeking to align technological governance with societal values in an era of rapid AI advancement.

翻译：本文通过分析约90,000条推文和新闻报道，采用基于Transformer的自然语言处理模型，建立了2006年至2019年间六个欧洲国家对第四次工业革命（4IR）技术公众情感的经验基准，该时期早于生成式AI系统的广泛普及。研究发现，欧洲公共领域对技术变革的评价日益分化：在研究期间，中性情感显著下降，公众逐渐分化为热情支持与担忧两大阵营，这一模式在不同国家背景和技术领域中呈现显著差异。约6%的用户处于情感同质化的信息茧房网络中，其中隐私议题表现出最高的动态敏感性。这些发现为评估ChatGPT及后续生成式AI系统如何重塑公众关于自动化、就业与技术变革的讨论提供了方法论严谨的参考基准。研究结果对政策制定者在AI快速演进时代协调技术治理与社会价值具有重要启示。