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dc.contributor.authorYordanova, Kristina Y.
dc.contributor.authorDemiray, Burcu
dc.contributor.authorMehl, Matthias R.
dc.contributor.authorMartin, Mike
dc.date.accessioned2019-11-15T16:37:37Z
dc.date.available2019-11-15T16:37:37Z
dc.date.issued2019-03
dc.identifier.citationK. Y. Yordanova, B. Demiray, M. R. Mehl and M. Martin, "Automatic Detection of Everyday Social Behaviours and Environments from Verbatim Transcripts of Daily Conversations," 2019 IEEE International Conference on Pervasive Computing and Communications (PerCom, Kyoto, Japan, 2019, pp. 1-10. doi: 10.1109/PERCOM.2019.8767403en_US
dc.identifier.issn2474-2503
dc.identifier.doi10.1109/percom.2019.8767403
dc.identifier.urihttp://hdl.handle.net/10150/635986
dc.description.abstractCoding in social sciences is a process that involves the categorisation of qualitative or quantitative data in order to facilitate further analysis. Coding is usually a manual process that involves a lot of effort and time to produce codes with high validity and interrater reliability. Although automated methods for quantitative data analysis are largely used in social sciences, there are only a few attempts at automatically or semi-automatically coding the data collected in qualitative studies. To address this problem, in this work we propose an approach for automated coding of social behaviours and environments based on verbatim transcriptions of everyday conversations. To evaluate the approach, we analysed the transcripts from three datasets containing recordings of everyday conversations from: (1) young healthy adults (German transcriptions), (2) elderly healthy adults (German transcriptions), and (3) young healthy adults (English transcriptions). The results show that it is possible to automatically code the social behaviours and environments based on verbatim transcripts of the recorded conversations. This could reduce the time and effort researchers need to assign accurate codes to transcribed conversations.en_US
dc.description.sponsorshipGerman Research FoundationGerman Research Foundation (DFG) [YO 226/1-1]; University of Zurich's Digital Society Initiative in the context of the DSI Fellowships and Collegium Helveticumen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2019 IEEE.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectsocial behaviour analysisen_US
dc.subjectnatural language processingen_US
dc.subjectautomated codingen_US
dc.titleAutomatic Detection of Everyday Social Behaviours and Environments from Verbatim Transcripts of Daily Conversationsen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Dept Psycholen_US
dc.identifier.journal2019 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS (PERCOM)en_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal accepted manuscripten_US
refterms.dateFOA2019-11-15T16:37:38Z


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