Mental health awareness for Gen Z: a data-driven UGC analysis of humor as a collective coping mechanism in social media communication
Pinto, Giulia (A.A. 2022/2023) Mental health awareness for Gen Z: a data-driven UGC analysis of humor as a collective coping mechanism in social media communication. Tesi di Laurea in Data visualization, Luiss Guido Carli, relatore Blerina Sinaimeri, pp. 85. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Generation Z. Identikit and generational comparison. The interconnection between mental health issues and internet world. Intyernet memes culture. Birth and evolution: an ambiguous definition. Mental health memes: why are they so relatable? Methodology. Data collection and manipulation. Data cleaning. Textual data extraction and preprocessing. LDA topic modeling and trend analysis. Thematic analysis.
References
Bibliografia: pp. 70-72.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Data visualization |
| Thesis Supervisor: | Sinaimeri, Blerina |
| Thesis Co-Supervisor: | Finocchi, Irene |
| Academic Year: | 2022/2023 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 11 Jul 2024 13:20 |
| Last Modified: | 11 Jul 2024 13:20 |
| URI: | https://tesi.luiss.it/id/eprint/39316 |
Downloads
Downloads per month over past year
Repository Staff Only
 |
View Item |
