Project

Platforms for big data foresight

Goal: Funded by the Research Council of Lithuania with a budget of EUR 613'000, this project aims to create social innovation empowerment measures, based on big data and future foresights methodologies. The anticipated outcome result of the project – the big data platform for future foresights – is a tool for the identification and analysis of large-scale societal issues, the anticipation of future development scenarios, and the selection of appropriate strategies for decision-makers.

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Project log

Steffen Roth
added a research item
This paper explores the potential of big data, such as those compiled by the Google Books project, to inform the dominant theories of the firm that tend to be grounded on strong assumptions about the capitalist nature of the modern society. Combining the novel methodologies of the digital age with Niklas Luhmann's theory of functional differentiation, we draw on big data-driven abductive reasoning to redirect the attention of management scholars away from the dominant contract-based and competence theories of capitalist firms toward organizations navigating the regime of functional differentiation, which is marked by contingent and historically evolving prominence of individual function systems. We conclude that this navigation requires appropriate strategic management tools which are no longer primarily geared to the economic function system but rather entail a radical reconfiguration of the firm as a multifunctional organization.
Steffen Roth
added a research item
Seeking to advance a big data approach to social theory, Roth et al. (2017) applied the Google Ngram Viewer toexplore the way the evolution of the function systems of the modern society is reflected in the Google Bookscorpus. The authors produced a highly counterintuitivefinding that the modern Western societies cannot beadequately described as capitalist. In order to respond to the controversies raised by thisfinding, the presentarticle replicates Roth et al. (2017) study while using a superior plotting software that allows to control the riskthat keyword strength can be biased due to the neglect of keyword quantity. Covering the English-, French-, and German-language corpora, the present replication effort has confirmed the existence of distinct trends exhibitedby the individual function systems, such as secularization, the persistent dominance of the political system, andthe relatively lesser role of the economic system. These results are largely consistent with those of Roth et al.(2017) and thus lend credence to the authors’sceptical assessment of the validity of the capitalist semantics. The article concludes by pleading for the routinization of big data-driven checks of the modern social theories.
Steffen Roth
added a research item
Highlights • Foresights and futures studies depend on the adequacy of our knowledge of the present and the past. • Big data evidence suggests that the English language area was not capitalist between 1800 and 2000. • Popular social macro trend statements ought to be regularly scrutinised so as to reduce the risk that inadequate trend assumptions are projected into the future. Abstract: As foresights and futures studies depend on the pertinence of our knowledge of the present and the past, this article tests whether the English language area may be adequately described as secularised and capitalist between 1800 and 2000. We are using the Google Ngram Viewer to chart and interpret time series plots of combined frequencies of pertinent keywords in the largest Internet book corpus, the Google Books corpus. The results suggest that the English language area is a secularised, politicised, scientificised, and ultimately also mediatised language area which has never been dominated by the economy. We conclude that the sample period may not be characterised as capitalist if we associate capitalism with any form of over-average importance or even dominance of the economy and suggest that popular social macro trend statements be regularly turned from implicit assumptions into explicit research questions so as to reduce the risk that inadequate trend assumptions are projected into the future.
Steffen Roth
added a project goal
Funded by the Research Council of Lithuania with a budget of EUR 613'000, this project aims to create social innovation empowerment measures, based on big data and future foresights methodologies. The anticipated outcome result of the project – the big data platform for future foresights – is a tool for the identification and analysis of large-scale societal issues, the anticipation of future development scenarios, and the selection of appropriate strategies for decision-makers.