Adapting Data-Driven Research to the Fields of Social Sciences and the Humanities

Albert Weichselbraun, Philipp Kuntschik, Vincenzo Francolino, Mirco Saner, Urs Dahinden and Vinzenz Wyss
Additional contact information
Albert Weichselbraun: Institute for Information Research, University of Applied Sciences of the Grisons, 7000 Chur, Switzerland
Philipp Kuntschik: Institute for Information Research, University of Applied Sciences of the Grisons, 7000 Chur, Switzerland
Vincenzo Francolino: Institute for Information Research, University of Applied Sciences of the Grisons, 7000 Chur, Switzerland
Mirco Saner: IAM Institute of Applied Media Studies, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland
Urs Dahinden: Institute for Information Research, University of Applied Sciences of the Grisons, 7000 Chur, Switzerland
Vinzenz Wyss: IAM Institute of Applied Media Studies, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland

Future Internet, 2021, vol. 13, issue 3, 1-22

Abstract: 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.

Keywords: Big Data; Web Intelligence; media analytics; social sciences; humanities; linked open data; adaptation process; interdisciplinary research; media criticism (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1999-5903/13/3/59/pdf (application/pdf)
https://www.mdpi.com/1999-5903/13/3/59/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:13:y:2021:i:3:p:59-:d:506442

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().