Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Anees Moidheen, M.M.; Parande, Athreya S; Jomy, Rayal; Presannakumar, Krishna; Souza, Mithun D Title A name given to the resource Predictive Modeling of Substance Abuse Risks using Big Data Analytics and Social Media Mining Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings of the 2025 International Conference on Computational Innovations and Sustainable Technologies, ICCIST 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCIST67338.2025.11438824" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCIST67338.2025.11438824</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037460726?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037460726?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Anees Moidheen M.M., Department Of Computer Science, Christ (Deemed to be University) Bangalore Yeshwanthpur Campus, Bangalore, India; Parande A.S., Department Of Computer Science, Christ (Deemed to be University) Bangalore Yeshwanthpur Campus, Bangalore, India; Jomy R., Department Of Computer Science, Christ (Deemed to be University) Bangalore Yeshwanthpur Campus, Bangalore, India; Presannakumar K., Department Of Computer Science, Christ (Deemed to be University) Bangalore Yeshwanthpur Campus, Bangalore, India; Souza M.D., Department Of Computer Science, Christ (Deemed to be University) Bangalore Yeshwanthpur Campus, Bangalore, India Description An account of the resource The worldwide increase in substance abuse among teenagers and young adults has become serious concern in recent times. One way this pattern has developed is through the evolution of social media. Social media has transformed people's attitudes towards certain behaviors and has encouraged risky behavior to the point of actually causing addiction by exposing them to drug-related material. Despite the existence of preventative measures, such as education programs in schools, many children and youth have not had adequate access to educational interventions or evidence-based measures due to barriers created by geography, economic circumstances, and social factors, particularly in less developed countries. The research proposed is focusing on addressing this gap using a big data approach. This research employs a unique analytical framework that integrates multiple large data sets from a variety of sources to better identify and assess the effectiveness of interventions. This model employs an analytical approach that uses statistical learning techniques and predictive analytics to identify historical patterns and anticipate future trends, and assess the effectiveness of various interventions conducted in different countries. The results of the analysis suggest that this big data approach will provide decision-makers with clearly documented evidence related to various risk-taking behaviors as they relate to available prevention interventions, and will assist decision-makers in developing targeted prevention intervention strategies. This study demonstrates the revolutionary aspect behind the application of computational intelligence in preventing substance abuse and informing evidence-based community health interventions. 2025 IEEE. Subject The topic of the resource Addiction Prevention; Big Data Analytics; Predictive Modelling; Public Health Informatics; Risk Detection; Social Media Influence; Substance Abuse; Treatment Barriers Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833159676-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online