Mapping Digital Discussions on NEETs in Türkiye: An Analysis of YouTube Comments Using Text Mining and Inductive Content Analysis

Autori:

Oğuz KUŞ

Cod: ISSN: 1583-3410 (print), ISSN: 1584-5397 (electronic)
Dimensiuni: pp. 54-67

How to cite this article:

Kuş, O. (2025). Mapping Digital Discussions on NEETs in Türkiye: An Analysis of YouTube Comments Using Text Mining and Inductive Content Analysis. Revista de Cercetare si Interventie Sociala, 91, 54-67, DOI: 10.33788/rcis.91.3

Abstract:

Türkiye has a significant NEET population. However, there is a lack of research focusing on the discussions taking place on social media platforms. Content analysis of digital discussions concerning NEETs enables a deeper understanding of the forms of potential stigmatization they face, the extent of social empathy and solidarity surrounding them, and the possible underlying causes of NEET status. This exploratory study analyzes user comments under the most-watched Turkish-language YouTube videos about NEETs, using a Multilingual SBERT-based clustering algorithm and qualitative inductive content analysis. The findings revealed the factors contributing to NEET status, the experiences of NEETs, perspectives that promote empathy, gendered dimensions of being NEET and potential risks of stigmatization. In addition, based on the interaction metric, the study identified themes which are important for the users. The findings can support institutions, organizations and NGOs in policy development and help shape communication strategies for societal behavior change.