Ontological Related Application for Social Media
Sachin Mittal · 2024
Using social media platforms has become more popular as an extra means of communication for businesses to communicate with their employees, clients, and stakeholders. The degree of engagement noted on this communication channel corresponds to the amount of information that is significant to commercial enterprises. As a result, in addition to manual techniques, different processes must be used in order to monitor and analyze this data. In the fields of social media monitoring and social search, foundational approaches have been developed. Simple grammar structures and keyword-based searches are limited in what they can reveal and only provide preliminary clues. The significant costs associated with creating ontologies that are domain-specific represent one of the key obstacles to putting advanced ontology engineering techniques into practice. This specific issue has often made it more difficult for them to be used in various Social Media Analysis scenarios. This paper summarizes recent findings and proposes an automated information extraction approach from legacy corporate application systems to enhance the efficacy of ontology design. In order to achieve the intended goal, the current research attempts to assess the efficacy of well-established ontology engineering techniques and their combination with text mining tools. The ontology allows for flexible and effective monitoring and analysis of unformatted information by acting as a lexicon for disordered social media content analysis.