https://socictopen.socict.org/files/original/816c30e70459ea89a752dc911ac59aed.pdf e260aad812cf2847d697cafd3cb07b3a 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 Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. 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 Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification. Creator An entity primarily responsible for making the resource B N Ramya, Shyleshwari M Shetty, A M Amaresh, R Rakshitha Description An account of the resource In present modern era, the outbreak of COVID-19 pandemic has created informational crisis. The public sentiments collected from different reflexions (hashtags, comments, tweets, posts of twitter) are measured accordingly, ensuring different policy decisions and messaging are incorporated. The implementation demonstrates intuition in to the advancement of fear sentiment eventually as COVID-19 approaches maximum levels in the world, by making use of detailed textual analysis with the help of required text data visualization. In addition, technical outline of machine learning stratification approaches are provided in the frame of text analytics, and comparing their efficiency in stratifying coronavirus tweets of different lengths. Using Naïve Bayes method, 91% accuracy is achieved for short tweets and using logistic regression classification method, 74% accuracy is achieved for short tweets. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, Sentiment analysis, Tweet Identifier An unambiguous reference to the resource within a given context 10.1007/s42979-021-00625-5 Source A related resource from which the described resource is derived SN computer science