Juan Rafael Orozco-Arroyave
Biographic Data
| ID | 271977 |
|---|---|
| NAME | Juan Rafael Orozco-Arroyave |
| GIVEN NAMES | Juan Rafael |
| FAMILY NAME | Orozco-Arroyave |
| SIGNATURE | OROZCO-ARROYAVE J R |
| AFFILIATIONS | Universidad de Antioquia |
| ORCID | 0000-0002-8507-0782 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Mapping Poverty and Well-Being Through Natural Language Processing
Poverty and well-being indexes encompass dimensions that capture meaningful aspects of life worth measuring. These dimensions reflect people’s concerns and priorities, offering insight into their lived experiences. This study identifies dimensions of poverty and well-being directly from people’s everyday language and proposes a novel method for assigning weights to these dimensions based on what people express as important. Using topic modeling …
Identificación de la pobreza en Colombia: Comparación entre el índice de pobreza multidimensional y el sistema de identificación de beneficiarios de programas sociales
This study examines poverty identification in Colombia by comparing the multidimensional poverty index and the social program beneficiary identification system. The results are analyzed in Colombia and the City of Medellín using measures of agreement and a contingency table. A statistical learning model is employed to estimate the classification of the social program beneficiary identification system, achieving a balanced accuracy of 78%. Qualita…
Classification of Poverty Condition Using Natural Language Processing
Classification of Poverty Condition Using Natural Language Processing
Identificación de la pobreza en Colombia: Comparación entre el índice de pobreza multidimensional y el sistema de identificación de beneficiarios de programas sociales
This study examines poverty identification in Colombia by comparing the multidimensional poverty index and the social program beneficiary identification system. The results are analyzed in Colombia and the City of Medellín using measures of agreement and a contingency table. A statistical learning model is employed to estimate the classification of the social program beneficiary identification system, achieving a balanced accuracy of 78%. Qualita…
Mapping Poverty and Well-Being Through Natural Language Processing
Poverty and well-being indexes encompass dimensions that capture meaningful aspects of life worth measuring. These dimensions reflect people’s concerns and priorities, offering insight into their lived experiences. This study identifies dimensions of poverty and well-being directly from people’s everyday language and proposes a novel method for assigning weights to these dimensions based on what people express as important. Using topic modeling …
Computer Science (2 works) · Linguistics (2 works) · Natural language processing (2 works) · Political science (2 works) · Poverty (2 works) · Archaeology (1 works) · Artificial Intelligence (1 works) · Baseline (sea (1 works) · Boosting (machine learning (1 works) · Community Health and Development (1 works)