Twitter sentiment analysis & machine learning in threshold concept identification
Harrington, Susan and Dörfler, Viktor (2020) Twitter sentiment analysis & machine learning in threshold concept identification. In: BAM 2020: 34th Annual Conference of the British Academy of Management, 2020-09-02 - 2020-09-04, Cloud.
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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.
ORCID iDs
Harrington, Susan ORCID: https://orcid.org/0000-0001-7135-4613 and Dörfler, Viktor ORCID: https://orcid.org/0000-0001-8314-4162;-
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Item type: Conference or Workshop Item(Paper) ID code: 72609 Dates: DateEvent3 September 2020Published13 May 2020Accepted28 February 2020SubmittedSubjects: Philosophy. Psychology. Religion > Psychology Department: Strathclyde Business School > Management Science Depositing user: Pure Administrator Date deposited: 08 Jun 2020 14:59 Last modified: 11 Nov 2024 17:02 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/72609