Security Analysis in Ecuador: Advanced Integration of Geo-Positioning and Named Entity Recognition (G-NER) in X Platform Publications

In the contemporary information age, knowledge extraction from vast textual datasets become essential. Named Entity Recognition (NER) models emerge as fundamental tools for this task, focusing on identifying key elements, i.e., entities. This study is based on a ‘spaCy’s-es_core_news_lg’ NER model focusing on the geo-positioning of entities in publications related to security analysis in Ecuador. During increasing violence in the country, this work aims to improve situational awareness through NER models, enabling agile and effective responses from authorities. Geo-analysis of publications from the social network X (Twitter) is used, with a model that facilitates understanding through graphs, visualizing the distribution of security cases and violence in various sectors of Ecuador. The methodology adopted uses a modular pipeline, prioritizing the cleaning of text to enhance the precision of the results. The creation of density maps and spatial trend analysis supports the application of NER in the geolocation of entities. These results are anticipated to improve performance in critical areas such as trend analysis, information extraction, and thematic labeling, strengthening the ability to make informed decisions in crucial situations.