In this paper we report on an explorative study of the history of the twentieth century from a lexical point of view. As data, we use a diachronic collection of 270,000+ English-language articles harvested from the electronic archive of the well-known Time Magazine (1923-2006). We attempt to automatically identify significant shifts in the vocabulary used in this corpus using efficient, yet unsuper-vised computational methods, such as Parsimonious Language Models. We offer a qualitative interpretation of the outcome of our experiments in the light of momentous events in the twentieth century, such as the Second World War or the rise of the Internet. This paper follows up on a recent string of frequentist approaches to studying cultural history ('Culturomics'), in which the evolution of human culture is studied from a quantitative perspective, on the basis of lexical statistics extracted from large, textual data sets.
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