Assessing place experiences in Luton and Darlington on Twitter with topic modelling and AI-generated lexicons
Issued Date
2023-01-01
Resource Type
ISSN
17538335
eISSN
17538343
Scopus ID
2-s2.0-85165877576
Journal Title
Journal of Place Management and Development
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Place Management and Development (2023)
Suggested Citation
Taecharungroj V., Stoica I.S. Assessing place experiences in Luton and Darlington on Twitter with topic modelling and AI-generated lexicons. Journal of Place Management and Development (2023). doi:10.1108/JPMD-04-2023-0041 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/88209
Title
Assessing place experiences in Luton and Darlington on Twitter with topic modelling and AI-generated lexicons
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
Purpose: The purpose of this paper is to examine and compare the in situ place experiences of people in Luton and Darlington. Design/methodology/approach: The study used 109,998 geotagged tweets from Luton and Darlington between 2020 and 2022 and conducted topic modelling using latent Dirichlet allocation. Lexicons were created using GPT-4 to evaluate the eight dimensions of place experience for each topic. Findings: The study found that Darlington had higher counts in the sensorial, behavioural, designed and mundane dimensions of place experience than Luton. Conversely, Luton had a higher prevalence of the affective and intellectual dimensions, attributed to political and faith-related tweets. Originality/value: The study introduces a novel approach that uses AI-generated lexicons for place experience. These lexicons cover four facets, two intentions and two intensities of place experience, enabling detection of words from any domain. This approach can be useful not only for town and destination brand managers but also for researchers in any field.