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dc.contributor.authorChristensen, Kasper
dc.contributor.authorNørskov, Sladjana
dc.contributor.authorFrederiksen, Lars
dc.contributor.authorScholderer, Joachim
dc.date.accessioned2018-02-07T08:04:15Z
dc.date.available2018-02-07T08:04:15Z
dc.date.created2017-06-28T13:31:08Z
dc.date.issued2017
dc.identifier.citationCreativity and Innovation Management. 2017, 26 (1), 17-30.nb_NO
dc.identifier.issn0963-1690
dc.identifier.urihttp://hdl.handle.net/11250/2483117
dc.description.abstractOnline communities are attractive sources of ideas relevant for new product development and innovation. However, making sense of the ‘big data’ in these communities is a complex analytical task. A systematic way of dealing with these data is needed to exploit their potential for boosting companies' innovation performance. We propose a method for analysing online community data with a special focus on identifying ideas. We employ a research design where two human raters classified 3,000 texts extracted from an online community, according to whether the text contained an idea. Among the 3,000, 137 idea texts and 2,666 non-idea texts were identified. The human raters could not agree on the remaining 197 texts. These texts were omitted from the analysis. The remaining 2,803 texts were processed by using text mining techniques and used to train a classification model. We describe how to tune the model and which text mining steps to perform. We conclude that machine learning and text mining can be useful for detecting ideas in online communities. The method can help researchers and firms identify ideas hidden in large amounts of texts. Also, it is interesting in its own right that machine learning can be used to detect ideas.
dc.language.isoengnb_NO
dc.titleIn Search of New Product Ideas: Identifying Ideas in Online Communities by Machine Learning and Text Miningnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersion
dc.source.pagenumber17-30nb_NO
dc.source.volume26nb_NO
dc.source.journalCreativity and Innovation Managementnb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.1111/caim.12202
dc.identifier.cristin1479550
dc.relation.projectNorges forskningsråd: 262303nb_NO
dc.relation.projectNofima AS: 201703nb_NO
cristin.unitcode7543,3,3,0
cristin.unitnameSensorikk, forbruker og innovasjon
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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