Prioridades de atención en zonas rurales en escenarios posconflicto: un análisis de minería de texto

Abstract

Automated text analysis tools summarize large volumes of information and allow efficient generation of insights from unstructured data such as opinions. The objective of this work was to identify priorities in communities affected by the armed conflict using participatory exercises in 13 municipalities of Antioquia, Colombia. 15,534 opinions from 9,765 people were analyzed. After a text cleaning, the use, association, differentiation and importance of the terms were described according to the thematic approaches and types of opinion expressed using text mining in R. It was found that the priorities revolved around the availability of infrastructures, endowment and inputs, since they were the most mentioned problems by the communities, and that this corresponded to the territorial reality. On the other hand, the opportunities were mainly represented by natural and human resources. The text mining analysis of the participatory exercise allowed to identify the priorities of the communities at the socioeconomic level in a satisfactory way. However, the preparation of the information is labor intensive and the results must be carefully reviewed to ensure consistency. Another advantage of this tool is that the information can be analyzed by external agents to the data collection.