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 Article Faculty Publications -Articles 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 Tripathi, Sachin; Tiwari, Akhilesh; Upreti, Kamal; Radhakrishnan, G.V. Title A name given to the resource A Machine Learning Approach to Consumer Behavior Analysis in Social Media-Influenced E-Book Markets 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 Journal of Applied Science and Technology Trends;Volume;6;Issue;2;pp.242-250 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.38094/jastt62318" target="_blank" rel="noreferrer noopener">https://doi.org/10.38094/jastt62318</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105016567771?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105016567771?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 Tripathi S., Department of Business and Management, Christ University, Delhi NCR Campus, Ghaziabad, India; Tiwari A., Department of Business and Management, Christ University, Delhi NCR Campus, Ghaziabad, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India; Radhakrishnan G.V., Kalinga School of Management, Kalinga Institute of Industrial Technology, Bhubaneswar, India Description An account of the resource Social media has emerged as a dominant marketing channel, significantly influencing consumer purchase decisions. Despite extensive global research, little is known about region-specific dynamics in emerging markets such as India. This study addresses this gap by applying Random Forest and Gradient Boosting models to survey data from 386 respondents in the Delhi-NCR region to analyze e-book purchasing behavior. Data were preprocessed through encoding, normalization, and stratified traintest splitting (80:20), with reproducibility ensured via a fixed random seed. Model evaluation employed R, RMSE, and MAE metrics, alongside a paired-sample t-test. Results showed that Gradient Boosting (R = 0.82) outperformed Random Forest (R = 0.78; p = 0.038). Feature importance analysis revealed that behavioral variablespurchase intention, brand awareness, and social media engagementwere the strongest predictors, whereas demographic features contributed minimally. These findings emphasize the primacy of behavioral traits in social mediadriven e-book markets and provide evidence for designing region-specific digital marketing strategies in emerging economies. 2025, Interdisciplinary Publishing Academia. All rights reserved. Subject The topic of the resource classification; Cognitive Learning; Education; Machine Learning; Non-cognitive Learning; student performance Publisher An entity responsible for making the resource available Interdisciplinary Publishing Academia Relation A related resource ISSN: 27080757; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online