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 Kundu, Seeboli Ghosh; Kundu, Avisek; Sahu, Santosh Kumar; Kalsi, Suchi; Siddhapura, Akshita; Badgayan, Nitesh Dhar Title A name given to the resource SentimentViz: Leveraging RoBERTa in Python for Advanced Sentiment Analysis and Decision-Making for a Famous Indian FMCG (Ayurvedic) Brand 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 Smart Innovation, Systems and Technologies;Volume;454 SIST;pp.517-529 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-032-07837-7_39" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-07837-7_39</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105036706993?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105036706993?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 Kundu S.G., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Bengaluru Campus, Pune, India; Kundu A., School of Business Management, Christ University, Bengaluru, India; Sahu S.K., School of Mechanical Engineering, VIT-AP University, Besides A.P. Secretariat, Andhra Pradesh, Amaravati, India; Kalsi S., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Bengaluru Campus, Pune, India; Siddhapura A., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Bengaluru Campus, Pune, India; Badgayan N.D., KPMG, Mumbai, India Description An account of the resource Indian consumer preferences for Ayurvedic brands increasingly turn to the marketplace for well-being. Ayurveda has a deep-rooted history in emerging economies like India, and its increasing role in health, wellness, and exports contributes to Indias economic development. The consumption and changing lifestyle patterns significantly contribute to achieving the United Nations Sustainable Development Goals (SDGs). The primary objective of this study is to explore consumer sentiment that includes perceptions, feelings, and attitudes toward these natural healthcare products contributing to specific SDG targets, leading to good health and well-being. In a data-driven world where governments and businesses seek insights from vast amounts of unstructured text data, sentiment analysis plays a pivotal role in decision-making. Sentiment analysis helps analyze different aspects of unstructured data, including customer experience and insights generated in terms of usage, challenges, and preferences and ultimately helps manage customer engagement. The sentiment analysis requires understanding the context, grouping similar words, removing unrelated content, and then gauging the sentiment of the text. There has always been a challenge to contextualize and gauze the deeper sentiments and create scalable solutions. To build on this need for deeper sentiment understanding and scalable solutions, SentimentViz is a proposed accelerator as part of this paper that leverages Python and chooses the best methodology for text-mining problems. It enables real-time analysis with robust visualization capabilities: In this study, the SentimentViz accelerator is leveraged to estimate the sentiment of 9 products using a robust data science framework and best-of-the-class ML techniques. The detailed consumer sentiment analysis helped to develop a deeper understanding of the value of FMCG (Ayurvedic products) for an emerging economy like India. This will help marketers build targeted marketing campaigns, brand health monitoring, and customer retention strategies through informed decisions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. Subject The topic of the resource Decision-making; Marketing analytics; Natural language processing; Real-time analysis; Sentiment analysis Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 21903018; ISBN: 978-303207836-0; 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