Detección Temprana de Riesgos de Aparición de Trastornos Adictivos de Juego mediante Minería Web con Modelos Avanzados de Búsqueda y Procesamiento de Lenguaje Natural

Nowadays, a number of psychological disorders are having a significant impact on our society. Gambling disorders were included in the International Classification of Diseases (ICD-11), published by the World Health Organization (WHO) in 2018, in response to the growing international concern in this area. In recent years, there has been an increasing recognition that patterns associated with gambling can lead to dysfunction and psychological distress for some gamblers, and in several countries, this issue has raised significant public health concerns. Despite the severity of these disorders, in many cases, individuals do not receive treatment or receive late treatment.

There are well-documented limitations of existing preventive instruments and a need for new instruments that distinguish across the spectrum of gambling behaviors, including various scenarios such as 'regular and healthy gambling behaviors,' 'problem gambling' or 'gambling disorder'. The non-identification or late identification of signs of gambling disorders leads to serious social, health, and economic costs. This also has a significantly concerning impact on the adolescent population.

Language and the way people express themselves are powerful indicators of personality traits, emotions, and provide valuable clues about the mental health and disorders of individuals. We can find distinctive psychological patterns in individuals not only by analyzing the topics they discuss but also by studying how they use language connectors such as prepositions or pronouns


The main objective of this project is to develop the necessary technologies and computational models for conducting large-scale natural language analysis (NLP). It involves designing and implementing new monitoring and analysis tools that can, based on publicly available web information, perform content mining to extract traces and evidence related to gambling disorders. More specifically, the primary goal is to study how people use language (and the evolution of NLP usage) to reveal early signs of gambling-related disorders.