Using Computational Grounded Theory to Understand Tutors’ Experiences in the Gig Economy

Lama Alqazlan, Rob Procter, Michael Castelle


Abstract
The introduction of online marketplace platforms has led to the advent of new forms of flexible, on-demand (or ‘gig’) work. Yet, most prior research concerning the experience of gig workers examines delivery or crowdsourcing platforms, while the experience of the large numbers of workers who undertake educational labour in the form of tutoring gigs remains understudied. To address this, we use a computational grounded theory approach to analyse tutors’ discussions on Reddit. This approach consists of three phases including data exploration, modelling and human-centred interpretation. We use both validation and human evaluation to increase the trustworthiness and reliability of the computational methods. This paper is a work in progress and reports on the first of the three phases of this approach.
Anthology ID:
2021.nlp4dh-1.13
Volume:
Proceedings of the Workshop on Natural Language Processing for Digital Humanities
Month:
December
Year:
2021
Address:
NIT Silchar, India
Editors:
Mika Hämäläinen, Khalid Alnajjar, Niko Partanen, Jack Rueter
Venue:
NLP4DH
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
111–120
Language:
URL:
https://aclanthology.org/2021.nlp4dh-1.13
DOI:
Bibkey:
Cite (ACL):
Lama Alqazlan, Rob Procter, and Michael Castelle. 2021. Using Computational Grounded Theory to Understand Tutors’ Experiences in the Gig Economy. In Proceedings of the Workshop on Natural Language Processing for Digital Humanities, pages 111–120, NIT Silchar, India. NLP Association of India (NLPAI).
Cite (Informal):
Using Computational Grounded Theory to Understand Tutors’ Experiences in the Gig Economy (Alqazlan et al., NLP4DH 2021)
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PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/2021.nlp4dh-1.13.pdf