Publicação
Mental health at Nova SBE
| Resumo: | This research tackles the understanding of the leading drivers affecting mental health amongst Nova SBE students during Covid-19. The objective behind the study is to identify the groups of students with the highest risk of suffering from poor mental health, in order to achieve measures of prevention corresponding to where they may suffer the most. The dataset is composed of three similar surveys forwarded to students in separate times of the academic year 2021-2022. I will be using unsupervised clustering algorithms on the data to fixate newly formed groups of students sharing the same similarity traits based on the frameworks of the surveys. The results will be leveraged using analytical and descriptive techniques to serve the purpose of the study. The main tool used in this research is Python programming language, mainly chosen for the implementation of the material covered during my master’s degree, and for the flexibility of using the different packages and libraries (Pandas, NumPy, Matplotlib, Scikit-learn). |
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| Autores principais: | Ahrach, Bilal El |
| Assunto: | Mental health Students Clustering algorithms Prevention |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This research tackles the understanding of the leading drivers affecting mental health amongst Nova SBE students during Covid-19. The objective behind the study is to identify the groups of students with the highest risk of suffering from poor mental health, in order to achieve measures of prevention corresponding to where they may suffer the most. The dataset is composed of three similar surveys forwarded to students in separate times of the academic year 2021-2022. I will be using unsupervised clustering algorithms on the data to fixate newly formed groups of students sharing the same similarity traits based on the frameworks of the surveys. The results will be leveraged using analytical and descriptive techniques to serve the purpose of the study. The main tool used in this research is Python programming language, mainly chosen for the implementation of the material covered during my master’s degree, and for the flexibility of using the different packages and libraries (Pandas, NumPy, Matplotlib, Scikit-learn). |
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