Sensitizing Social Interaction with a Mode-Enhanced Transcribing Process

Qian Li

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
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Qualitative researchers often work with texts transcribed from social interactions such as interviews, meetings, and presentations. However, how we make sense of such data to generate promising cues for further analysis is rarely discussed. This article proposes mode-enhanced transcription as a tool for sensitizing social interaction data, defined as a process in which researchers attune their attention to the dynamic interplay of verbal and nonverbal features, expressions, and acts when transcribing and proofreading professional transcripts. Two scenarios for using mode-enhanced transcription are introduced: sensitizing previously collected data and engaging with modes purposefully. Their implications for research focus, data collection, and data analysis are discussed based on a demonstration of the process with a previously collected dataset and an illustrative review of published articles that display mode-enhanced excerpts. The article outlines the benefits and further considerations of using mode-enhanced transcription as a sensitizing tool.
Original languageEnglish
Number of pages26
JournalOrganizational Research Methods
Publication statusE-pub ahead of print - 31 Oct 2022


  • transcribing
  • sensitization
  • multimodality
  • qualitative research
  • interpretivism
  • qualitative content
  • semiotic analysis


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