Children in-conflict chatbot system using natural language processing technique

Abstract

Chatbot support system aimed at addressing smoking and drinking behavior among juveniles through the application of natural language processing (NLP) techniques. Juvenile smoking and drinking have become pressing concerns in society, necessitating effective interventions to curb these behaviors. Traditional methods of counseling and intervention often face limitations in reaching and engaging with young individuals. Leveraging advancements in NLP, the proposed chatbot system offers an alternative approach for counseling and support. The system incorporates a comprehensive understanding of the underlying causes and motivations behind the delinquent behaviors, allowing the chatbot to engage in meaningful conversations with the juveniles. By employing NLP algorithms, the chatbot analyzes and interprets the language used by the individuals, providing tailored responses and guidance. The development process involves data collection from juveniles in conflict, constructing a knowledge base, training the chatbot model, and validating its effectiveness through user feedback and evaluation. Preliminary results indicate promising outcomes in terms of engagement, acceptance, and efficacy. The chatbot support system holds the potential to serve as a valuable tool in addressing smoking and drinking behaviors among juveniles, providing accessible and personalized support to help them make healthier choices. Further research and refinement of the system are necessary to enhance its accuracy, adaptability, and overall impact in real-world scenarios.