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 Tiwari, Aayush; Maitra, Diyotrim; Wagh, Rupali S. Title A name given to the resource Decoding the Impact of Social Media on IPL Player Retention Using Sentiment Analysis and Ensemble Learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1612 LNNS;pp.459-475 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-95-2872-1_33" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-95-2872-1_33</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028326439?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028326439?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 Tiwari A., CHRIST University, Bengaluru, India; Maitra D., CHRIST University, Bengaluru, India; Wagh R.S., CHRIST University, Bengaluru, India Description An account of the resource This research query contrasted the use of player performance measures and fan sentiment rating scores in predicting player retention in the Indian Premier League (IPL). With the use of quantitative variables such as batting averages and bowling economies and qualitative variables including sentiment and visibility scores in over 1000 Reddit comments and posts, the research utilizes machine learning algorithms such as the Balanced Random Forest Classifier and Easy Ensemble Learning algorithms for enhancing decision-making on retention. In contrast to earlier approaches, which have largely disregarded the role of retention decision-making and qualitative data use in this context, the present study closes this gap by combining fan sentiment measures with visibility. The findings show that although conventional metrics hold, public opinion and sentiment have increasingly become factors in retention policy, particularly in the recent past. The highest performing model, which is a blend of both qualitative and quantitative traits, has an overall accuracy of 88%. The study finds the shift toward a more holistic, integrated approach, with the focus being on the data-driven nature of IPL team management for marketability, off-field pertinence, and on-field performance. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Cricket; Ensemble learning; IPL; Retention; Sentiment analysis Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981952871-4; 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