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.
Acknowledgements
I would like to thank Elizabeth Stokoe and Charles Antaki for their advice at various stages of writing this article.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1. At the time of data collection, Facebook chat was a quasi-synchronous means of interacting with others online. After data collection was completed, Facebook combined the asynchronous private messaging and quasi-synchronous chat features.