Data-driven analysis and prediction of norm acceptance
Data-driven analysis and prediction of norm acceptance
That norms matter for politics is a widely shared observation. Existing political science research on norm diffusion, norm localization, and contestations is, however, constrained due to methodological manageability of empirical data. To face this research challenge, we propose an interdisciplinary research collaboration between political and computer science. Using the show case of energy politics, we want to conduct unsupervised and semi-supervised content analysis and fusion with the help of automated text mining methods to analyze the influence of different types of so-called norm entrepreneurs on the public acceptance and, respectively, contestations of different energy policies.
240-245
Krestel, Ralf
70098425-7c94-4c29-885f-478715858816
Kuhn, Annegret
ac0b4e04-adb1-4c0a-bcbf-10af0b844413
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
20 July 2022
Krestel, Ralf
70098425-7c94-4c29-885f-478715858816
Kuhn, Annegret
ac0b4e04-adb1-4c0a-bcbf-10af0b844413
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Krestel, Ralf, Kuhn, Annegret and Hasselbring, Wilhelm
(2022)
Data-driven analysis and prediction of norm acceptance.
Informatik-Spektrum, 45 (4), .
(doi:10.1007/s00287-022-01472-1).
Abstract
That norms matter for politics is a widely shared observation. Existing political science research on norm diffusion, norm localization, and contestations is, however, constrained due to methodological manageability of empirical data. To face this research challenge, we propose an interdisciplinary research collaboration between political and computer science. Using the show case of energy politics, we want to conduct unsupervised and semi-supervised content analysis and fusion with the help of automated text mining methods to analyze the influence of different types of so-called norm entrepreneurs on the public acceptance and, respectively, contestations of different energy policies.
Text
s00287-022-01472-1
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Accepted/In Press date: 14 June 2022
Published date: 20 July 2022
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© 2022, The Author(s).
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Local EPrints ID: 488941
URI: http://eprints.soton.ac.uk/id/eprint/488941
ISSN: 0170-6012
PURE UUID: 7c731dd8-9b0c-4d4c-8a70-f2c531709ac1
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Date deposited: 09 Apr 2024 17:09
Last modified: 10 Apr 2024 02:15
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Contributors
Author:
Ralf Krestel
Author:
Annegret Kuhn
Author:
Wilhelm Hasselbring
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