In this article, we explore the social impact of technology in contemporary societies using a dataset of multilingual newspapers in English, French, Spanish, Italian, and German. Our observational time covers twenty years (1999-2018). We filter documents using four technological key terms: nuclear, oil, internet, and automation, that we consider as proxies reflecting Smil 2006 taxonomy of technology. Our methodology is formed by a five-step pipeline: Topic modelling (Pachinko Allocation), word embeddings, Ward’s hierarchical cluster analysis, network analysis, and sentiment analysis. We analyze information stability (which we define as low levels of semantic diversity in our data outcomes over time at the individual key term level) and information homogeneity (which we understand as low levels of semantic diversity in our data outcomes across our selection of key terms). We seek to observe to what extent our selection of key terms permeates into press discourses similarly or differently, and whether those discourses fall into semantic categories that could be considered as essential elements of the fabric of contemporary societies (such as finance, education, or politics). Results show, firstly, a consistent overlap of content across newspapers’ semantic fields that could be considered as pillars of society. Secondly, we notice a progressive simplification of information historically, reflecting less polarizing views across countries and, therefore, demonstrating an increasing agreement on technologically related discourses. We interpret these results as an indicator of the rising intrusion of technology in Western, industrialized countries.
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