António, Nuno Miguel da ConceiçãoJaklič, JurijAbouljid, Younes2024-03-262024-03-262024-02-09http://hdl.handle.net/10362/165444Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThis research aims to elucidate the factors that drive engagement with video-centric social media content, focusing on the cognitive appraisal of such content. This study employs sentiment analysis, utilizing the analytical capabilities of Power BI to interpret data gathered through OpenCV machine learning models and user feedback surveys. The objective is to discern the emotional responses elicited by different types of engagement. The data collected from various sources was synthesized and standardized to uncover patterns, correlations, and key determinants of social media engagement and the emotions it triggers. By gaining insights into the emotional aspects triggered by media content, campaign managers can more effectively design and test their campaigns prior to deployment, thereby enhancing engagement and mitigating potential shortcomings.engSentiment analysiscognitive appraisalsocial mediacustomer engagementemotional responsevideo contentSDG 4 - Quality educationSDG 8 - Decent work and economic growthSDG 9 - Industry, innovation and infrastructuremaster thesis203557956