Abstract
Transcription of audio data is widespread in qualitative research, with transcription of video data also becoming common. Online data is now being collected using screen-capture or video software, which then needs transcribing. This paper draws together literature on transcription of spoken interaction and highlights key transcription principles, namely reflecting the methodological approach, readability, accessibility, and usability. These principles provide a framework for developing a transcription system for multi-modal text-based data. The process of developing a transcription system for data from Facebook chat is described and reflected on. Key issues in the transcription of multi-modal text-based data are discussed, and examples provided of how these were overcome when developing the transcription system.
Highlights
A recent development in qualitative research has been the growing interest in online textbased data, such as online chats, e-mails, text messages, instant messaging interactions and so on (e.g., Baym, 2009; Coulson, 2005; Herring, 2007)
This paper has demonstrated how a framework of transcription principles can be used for developing a transcription system for text-based multi-modal data
The aim of this paper was to demonstrate how text-based multi-modal data can be transcribed using a framework of transcription principles
Summary
A recent development in qualitative research has been the growing interest in online textbased data, such as online chats, e-mails, text messages, instant messaging interactions and so on (e.g., Baym, 2009; Coulson, 2005; Herring, 2007). While much of this data does not need to be transcribed, some online data is being collected using screen-capture software (Bhatt & de Roock, 2013), which records actions occurring on a computer screen. While most of the literature has focused on transcribing spoken language, a growing literature discusses how to transcribe physical aspects of an interaction, such as body language, gaze, gesture and so on
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