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Informing policy with text mining: technological change and social challenges

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dc.abstract.enThis study presents an innovative text mining methodology that supports policy analysts with problem recognition, definition and selection. The empirical analysis is based on four years of online news articles published in the period 2016–2019. Using a combination of text mining methods (analysis of term-frequencies, co-occurrence and sentiment analysis), we identify trending terms and explore selected regulatory issues. The analysis demon- strates that while each text mining algorithm provides insightful results, their combination yields more detailed and robust overview of regulatory problems. The results present early signals and trends, the connections between trending topics, and the changing public atti- tudes towards them.
dc.affiliationUniwersytet Warszawski
dc.contributor.authorNawaro, Łukasz
dc.contributor.authorPaliński, Michał
dc.contributor.authorGyódi, Kristóf
dc.contributor.authorWilamowski, Maciej
dc.date.accessioned2024-01-25T04:14:28Z
dc.date.available2024-01-25T04:14:28Z
dc.date.copyright2022-04-16
dc.date.issued2022
dc.description.accesstimeAT_PUBLICATION
dc.description.financePublikacja bezkosztowa
dc.description.versionFINAL_PUBLISHED
dc.identifier.doi10.1007/S11135-022-01378-W
dc.identifier.issn0033-5177
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/109304
dc.identifier.weblinkhttps://link.springer.com/content/pdf/10.1007/s11135-022-01378-w.pdf
dc.languageeng
dc.pbn.affiliationeconomics and finance
dc.relation.ispartofQuality and Quantity
dc.rightsCC-BY
dc.sciencecloudnosend
dc.subject.enTechnological policy
dc.subject.enOnline news
dc.subject.enText mining
dc.subject.enSentiment analysis
dc.titleInforming policy with text mining: technological change and social challenges
dc.typeJournalArticle
dspace.entity.typePublication