Alcohol Consumption

Research on alcohol consumption is increasingly focused on understanding and mitigating its negative impacts, particularly concerning excessive drinking and its societal consequences. Current studies utilize diverse approaches, including social network analysis with semantic technologies to model individual and community drinking patterns, and machine learning algorithms (e.g., hyperdimensional computing, various supervised and unsupervised methods) to analyze data from diverse sources like mobile phone location data and health surveys, improving the accuracy of risk assessment and intervention strategies. These advancements offer the potential for more effective personalized interventions and public health policies aimed at reducing alcohol-related harm.