Sensing Users Emotional Intelligence in Social Networks

Abstract

In this age of constant digital communication and social interaction, people are paying a lot of attention to how users' emotional intelligence affects their interactions and well-being on social networks. This research investigates the application of information systems and telecommunications technologies in the detection and analysis of users' emotional intelligence within the realm of social networks. The concept of emotional intelligence, which involves the capacity to notice, comprehend, regulate, and use emotions in a proficient manner, has significant importance in influencing encounters and relationships in the online domain. This article explores potential models of emotional intelligence based on sentiment analysis of social network data. Self-awareness, self-regulation, intrinsic motivation, and interpersonal connections are based on four principles. These four-dimensional models aggregate four numerical indicators to quantify emotional quotient. This study uses Twitter, a popular social network, to predict emotional intelligence in individuals or groups. This finding assesses users' emotional intelligence using four variables and shows their positive, negative, and neutral sentiments. The program we are developing is based on uploading Twitter datasets and forecasting emotional intelligence using algorithms and tools based on tweets, retweets, and followers, among other scenarios. The four dimensions allow us to feel emotions. Twitter datasets are in text files with JSON data.