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.
|Number of pages||7|
|Publication status||Published - 3 Sep 2020|
|Event||BAM 2020: 34th Annual Conference of the British Academy of Management - Cloud, United Kingdom|
Duration: 2 Sep 2020 → 4 Sep 2020
|Conference||BAM 2020: 34th Annual Conference of the British Academy of Management|
|Abbreviated title||BAM 2020|
|Period||2/09/20 → 4/09/20|
- sentiment analysis
- lived experience
- machine learning
Harrington, S., & Dörfler, V. (2020). 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.