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Automatic Detection of Everyday Social Behaviours and Environments from Verbatim Transcripts of Daily Conversations


Yordanova, Kristina Y; Demiray, Burcu; Mehl, Matthias R; Martin, Mike (2019). Automatic Detection of Everyday Social Behaviours and Environments from Verbatim Transcripts of Daily Conversations. In: 2019 IEEE International Conference on Pervasive Computing and Communications (PerCom), Kyoto, Japan, 11 March 2019 - 15 March 2019, 242-251.

Abstract

Coding 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.

Abstract

Coding 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.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
08 Research Priority Programs > Digital Society Initiative
08 Research Priority Programs > Dynamics of Healthy Aging
Dewey Decimal Classification:150 Psychology
Language:English
Event End Date:15 March 2019
Deposited On:20 Jan 2020 16:51
Last Modified:20 Jan 2020 20:30
Publisher:IEEE
ISBN:9781538691489
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/percom.2019.8767403
Official URL:https://ieeexplore.ieee.org/document/8767403

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