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 Pawar, Varsha; Jose, Deepa V. Title A name given to the resource Analysing Twitter User Behaviour with Process Mining: A Study on Activity Patterns 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 Lecture Notes in Networks and Systems;Volume;1240 LNNS;pp.395-403 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-1264-2_35" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-1264-2_35</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013373754?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013373754?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 Pawar V., Department of Computer Applications, CMR Institute of Technology, Bengaluru, India, Christ University, Bangalore, India; Jose D.V., Christ University, Bangalore, India Description An account of the resource Social media sites provide a platform to share the information. People share their views and interests. Social media data provides information on user, activity, network, and content. Researchers anticipate a lot of information from social media data. It covers the activities of user, people connected to them, and their likes and dislikes. If users data is processed keenly, one can easily understand a users behaviour with his actions and predicts the next action of the user. It also helps in describing the relations among the users. This study illustrated the process mining algorithms to uncover the insights of Twitter users data. The model depicts the overall process flow of Twitter user activities. Behavioural patterns like common sequences, repeated user actions, direct relations, and rare interactions are analysed. The models performance is assessed with the metrics like fitness, precision, and simplicity to choose the best model for the dataset. Inductive miner outperformed well with other algorithms. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Behaviour analysis; Process mining; Twitter; User behaviour Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981961263-5; 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