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 Conference Papers 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/. Title A name given to the resource Social Media Sentiment Analysis of Stock Market on Tweets Subject The topic of the resource analyze; estimate; machine learning; recommendation system; sentiment analysis Description An account of the resource Sentiment categorization is utilized in today's world to analyze social media data about the stock market and estimate its future stock movement. We investigated the possible influence of 'public sentiment' on 'market trends' using sentiment analysis and machine learning concepts. Due to the enormous number of components involved, such as economic situations, political events, and other environmental factors that may affect the stock price, stock price prediction is an exceedingly complicated and challenging process. Because of these considerations, evaluating a single factor's influence on future pricing and trends is challenging. As more individuals spend time online, the popularity and impact of numerous social media platforms has skyrocketed in recent years. Twitter is one such social media tool that has exploded in popularity. Twitter is a terrific place to stay up to speed on current societal trends and perspectives. The 'Twittersphere' is a melting pot that supports diverse viewpoints, emotions, and trends, and it has the potential to be a crucial influencer in influencing and shaping perceptions. 2022 IEEE. Creator An entity primarily responsible for making the resource Yadav K.; Vijayalakshmi S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 1977-1980. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823529" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823529</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135442240&amp;doi=10.1109%2FICACITE53722.2022.9823529&amp;partnerID=40&amp;md5=a3b07ae1f9de5c319a6bde91d9ef3420" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135442240&amp;doi=10.1109%2fICACITE53722.2022.9823529&amp;partnerID=40&amp;md5=a3b07ae1f9de5c319a6bde91d9ef3420</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Yadav K., Christ University, Dept. of Data Science, Maharashtra, Pune, India; Vijayalakshmi S., Christ University, Dept. of Data Science, Maharashtra, Pune, India