Sentiment analysis of buy now pay later (BNPL) application reviews as indicators of consumer trust in digital lending platforms.
The advent and mass adoption of digital lending and buy now pay later (BNPL) applications have metamorphosed how consumers take instant credit, making trust a salient determinant of lasting use and engagement. This study investigates how consumer sentiments, as expressed in user reviews of fintech l...
| Publicado en: | SHS Web of Conferences Vol. 230; pp. 1 - 19 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
EDP Sciences
4/10/2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=193893918&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 193893918 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24165182 FT5R jtl: SHS Web of Conferences issn: 24165182 maglogo: N pubinfo: dt: 4/10/2026 vid: 230 pid: 76090 pub: EDP Sciences artinfo: ui: 193893918 10.1051/shsconf/202623003002 ppf: 1 ppct: 18 formats: tig: atl: Sentiment analysis of buy now pay later (BNPL) application reviews as indicators of consumer trust in digital lending platforms. aug: au: Vohra, Antra Purohit, Sonal affil: Symbiosis Institute of Business Management, Nagpur, Symbiosis International (Deemed) University, Pune sug: keyword: Buy Now Pay Later (BNPL) Consumer Trust Digital Lending Fintech Sentiment Analysis ab: The advent and mass adoption of digital lending and buy now pay later (BNPL) applications have metamorphosed how consumers take instant credit, making trust a salient determinant of lasting use and engagement. This study investigates how consumer sentiments, as expressed in user reviews of fintech lending applications, can serve as an indicator of consumer trust in digital financial platforms, in light of the Integrative Model of Organizational Trust. The study will utilize publicly available recent and viable reviews from the Google Play Store and Apple App Store for two prominent digital lending applications. Sentiment Analysis techniques will be employed to classify these reviews into positive and negative trust brackets, while keyword clustering and thematic grouping will be used to identify factors influencing trust, such as service quality, transparency of charges, security, and customer support responsiveness. The findings aim to showcase how sentiment patterns reflect broader consumer perceptions of reliability, transparency, and platform credibility in the digital lending ecosystems. By linking the sentiment analytics with behavioral indicators of trust, this study contributes to advancing research on fintech adoption, digital financial inclusion, and consumer risk perception, offering practical learnings for fintech providers looking to enhance user confidence and prolonged engagement. pubtype: Conference Proceedings doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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