Twitter sentiment analysis & machine learning in threshold concept identification

Research output: Contribution to conferencePaper

Abstract

This paper discusses the proposed use of sentiment analysis and machine learning to explore threshold concepts. These moments of transformational learning exist only within the individual, making it essential to study them through lived experience. A combination of autoethnography, interviewing, and the afore-mentioned sentiment analysis and machine learning will be used to capture as wide a range of lived experiences as possible. In this particular study, the focus will be on autistic people, although, for the purposes of this developmental paper, the methods are considered more pertinent than the pool of participants. A brief introduction to autism is given purely for context, followed by a discussion of the proposed methods, including strengths and limitations.
Original languageEnglish
Number of pages7
Publication statusAccepted/In press - 13 May 2020
EventBAM 2020: 34th Annual Conference of the British Academy of Management - Cloud, United Kingdom
Duration: 2 Sep 20204 Sep 2020
https://www.bam.ac.uk/civicrm/event/info?id=3638

Conference

ConferenceBAM 2020: 34th Annual Conference of the British Academy of Management
Abbreviated titleBAM 2020
CountryUnited Kingdom
Period2/09/204/09/20
Internet address

Keywords

  • autism
  • sentiment analysis
  • Twitter
  • lived experience
  • machine learning

Cite this

Harrington, S., & Dörfler, V. (Accepted/In press). Twitter sentiment analysis & machine learning in threshold concept identification. Paper presented at BAM 2020: 34th Annual Conference of the British Academy of Management, United Kingdom.