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Analysis of the Relationship Between Self-Esteem and Depression


Affiliations
1 Faculty of Architecture, Universidad Autónoma de Puebla, Puebla, Mexico
2 Computer Science, Universidad Autónoma de Puebla, Puebla, Mexico
 

This article presents a comprehensive and in-depth analysis of the intricate relationship that underlies selfesteem and depression, two crucial aspects in the field of mental health. Study aims not only to scrutinize the existing relationship between self-esteem and depression but also to do so innovatively by leveraging the analytical and data visualization capabilities offered by two cutting-edge tools: Power BI [3], [4] and Weka [1], [2]. These platforms, widely recognized in the realm of data science, allow for not only exploring the relationship between these two fundamental variables but also presenting their findings in an accessible and enlightening manner for both specialized and general audiences. Thus, our study represents a comprehensive and multidisciplinary effort to unravel the complex relationship between self-esteem and depression. Through the synergy between advanced data analysis carried out with Weka and the powerful visualization provided by Power BI, the aim is not only to broaden the understanding of this crucial relationship but also to lay the groundwork for future research and approaches in the field of mental health. In a world where mental health takes center stage in socio-health concerns, this study aspires to contribute valuable insights that can inform and enrich the care, treatment, and policies related to depression and self-esteem.

Keywords

Data science, Depression, Self-esteem, Weka, Power-BI
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  • Analysis of the Relationship Between Self-Esteem and Depression

Abstract Views: 224  |  PDF Views: 73

Authors

Rosalba Cuapa C.
Faculty of Architecture, Universidad Autónoma de Puebla, Puebla, Mexico
Adair Ponce
Computer Science, Universidad Autónoma de Puebla, Puebla, Mexico
Meliza Contreras
Computer Science, Universidad Autónoma de Puebla, Puebla, Mexico
Mireya Tovar
Computer Science, Universidad Autónoma de Puebla, Puebla, Mexico
Fernando Zacarias F.
Computer Science, Universidad Autónoma de Puebla, Puebla, Mexico

Abstract


This article presents a comprehensive and in-depth analysis of the intricate relationship that underlies selfesteem and depression, two crucial aspects in the field of mental health. Study aims not only to scrutinize the existing relationship between self-esteem and depression but also to do so innovatively by leveraging the analytical and data visualization capabilities offered by two cutting-edge tools: Power BI [3], [4] and Weka [1], [2]. These platforms, widely recognized in the realm of data science, allow for not only exploring the relationship between these two fundamental variables but also presenting their findings in an accessible and enlightening manner for both specialized and general audiences. Thus, our study represents a comprehensive and multidisciplinary effort to unravel the complex relationship between self-esteem and depression. Through the synergy between advanced data analysis carried out with Weka and the powerful visualization provided by Power BI, the aim is not only to broaden the understanding of this crucial relationship but also to lay the groundwork for future research and approaches in the field of mental health. In a world where mental health takes center stage in socio-health concerns, this study aspires to contribute valuable insights that can inform and enrich the care, treatment, and policies related to depression and self-esteem.

Keywords


Data science, Depression, Self-esteem, Weka, Power-BI

References