ABSTRACT
With the growing popularity of unobtrusive research methods vis-à-vis the unprecedented increase of user-generated content (UGC), this investigation purports to populate the knowledge base on the emerging field of gerontalentology introduced by de Guzman, Mesana and Roman in 2020. Specifically, a qualitative sentiment analysis (QSA) was performed on social media expressions (n = 10,056) that were extracted from top-viewed YouTube videos (n = 12) via Data Miner, involving older adults auditioning in Got Talent®. The intensity of emotions or sentiments of online viewers was examined through with-in and cross-case analyses of posted comments. The process of constant comparison of field texts afforded the emergence of distinct and interesting depreciative, inspirative, appreciative, and emulative spaces that typify how older adults and their showcase of talents are individually and collectively viewed by the global audience. Implications of the study to promoting intergenerational contact of younger adults with older adults and the promises of gerontalentogical studies are also discussed in this paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was supported by the University of Santo Tomas [N/A].