Adapting data-driven research to the fields of social sciences and the humanities

MDPI 2021-03-04T10:24:41Z 2021-03-04T10:24:41Z 2021-02

Recent developments in the fields of computer science, such as advances in the areas of big data, knowledge extraction, and deep learning, have triggered the application of data-driven research methods to disciplines such as the social sciences and humanities. This article presents a collaborative, interdisciplinary process for adapting data-driven research to research questions within other disciplines, which considers the methodological background required to obtain a significant impact on the target discipline and guides the systematic collection and formalization of domain knowledge, as well as the selection of appropriate data sources and methods for analyzing, visualizing, and interpreting the results. Finally, we present a case study that applies the described process to the domain of communication science by creating approaches that aid domain experts in locating, tracking, analyzing, and, finally, better understanding the dynamics of media criticism. The study clearly demonstrates the potential of the presented method, but also shows that data-driven research approaches require a tighter integration with the methodological framework of the target discipline to really provide a significant impact on the target discipline.

Medienkritik; Automatisierte Inhaltsanalyse; WebLyzard; Big data; Web intelligence; 006: Spezielle Computerverfahren; 302.23: Medien; Beitrag in wissenschaftlicher Zeitschrift; Text

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CHZHA oai:digitalcollection.zhaw.ch:11475/21920
https://doi.org/10.3390/fi13030059
https://doi.org/10.21256/zhaw-21920
info:doi/10.3390/fi13030059
info:doi/10.21256/zhaw-21920
https://hdl.handle.net/11475/21920
https://digitalcollection.zhaw.ch/handle/11475/21920
info:hdl/11475/21920
urn:issn:1999-5903
1242405362

ZHAW UNIV LIBR
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