Assessing place experiences in Luton and Darlington on Twitter with topic modelling and AI-generated lexicons
Issue Date
2023-07-28Subjects
LDAplace analytics
GPT-4
place experience
generative AI
Subject Categories::G700 Artificial Intelligence
Metadata
Show full item recordAbstract
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.Citation
Taecharungroj V, Stoica IS (2024) 'Assessing place experiences in Luton and Darlington on Twitter with topic modelling and AI-generated lexicons', Journal of Place Management and Development, 17 (1), pp.49-73.Publisher
Emerald PublishingType
ArticleLanguage
enISSN
1753-8335EISSN
1753-8343ae974a485f413a2113503eed53cd6c53
10.1108/JPMD-04-2023-0041