English Speed Networking Conversational Transcripts
|Item Name:||English Speed Networking Conversational Transcripts|
|Author(s):||Kate Muir, Adam Joinson, Rachel Cotterill, Nigel Dewdney|
|LDC Catalog No.:||LDC2016T16|
|Release Date:||July 15, 2016|
|Data Source(s):||text chat conversations, microphone conversation|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2016T16 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Muir, Kate, et al. English Speed Networking Conversational Transcripts LDC2016T16. Web Download. Philadelphia: Linguistic Data Consortium, 2016.|
English Speed Networking Conversational Transcripts was developed at the University of the West of England and contains 388 transcripts of English face-to-face and instant messaging conversations about business ideas collected in 2014 and 2015 from participants (undergraduate students) playing different power roles.
This corpus was created to examine communication accommodation, specifically, the ways in which an individual's linguistic style, or how an individual communicates, is affected by social power and personality. The data was collected in two studies. In the first study, 40 participants had a series of paired five minute face-to-face conversations playing either a high, low or neutral power role. The same procedure was followed in the second study except that participants discussed business ideas via instant messaging.
The face-to-face conversations were audio-recorded and transcribed verbatim. There are 139 transcripts of conversations between high and low power individuals and 63 transcripts of conversations between neutral power individuals.
The instant messaging program automatically saved the transcripts of the messaging conversations; the transcripts were then retrieved and formatted for analysis. There are 85 transcripts of conversations between high and low power individuals and 101 transcripts of conversations between neutral power individuals.
The transcripts were anonymized. Gender and age metadata are available where provided.
All transcripts are presented as UTF-8 plain text files.
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