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Natural action processing conversation analysis and big interactional data

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conference contribution
posted on 07.01.2020, 09:47 by W Housley, Saul AlbertSaul Albert, Elizabeth StokoeElizabeth Stokoe
© 2019 Copyright held by the owner/author(s). This position paper identifies a crucial opportunity for the reciprocal exchange of methods, data and phenomena between conversation analysis (CA), ethnomethodology (EM) and computer science (CS). Conventional CS classification of sentiment, tone of voice, or personality do not address what people do with language or the paired sequences that organize actions into social interaction. We argue that CA and EM can innovate and substantially enhance the scope of the dominant CS approaches to big interactional data if artificial intelligence-based natural language processing systems are trained using CA annotated data to do what we call natural action processing.

History

School

  • Social Sciences

Published in

ACM International Conference Proceeding Series

Pages

34

Source

HTTF 2019: Proceedings of the Halfway to the Future Symposium 2019

Publisher

Association for Computing Machinery (ACM)

Version

AM (Accepted Manuscript)

Rights holder

© The Authors

Publisher statement

© Author 2019. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in HTTF 2019: Proceedings of the Halfway to the Future Symposium 2019, https://doi.org/10.1145/3363384.3363478

Publication date

2019-11-19

ISBN

9781450372039

Language

en

Editor(s)

Joel E Fischer; Sarah Martindale

Location

Nottingham

Event dates

Nov 19-20

Depositor

Dr Saul Albert Deposit date: 3 January 2020