A comparative analysis for identifying the polarity of people based on emotional pulse in a smart city

Abstract

Over the past decade, the field of industrial informatics has extensively studied smart-city applications. This paper proposes a method for identifying the polarity of people based on the emotional pulse of a city by using publicly available, large-scale social media interactions that capture individuals' ideas and beliefs. The effectiveness of the framework was assessed and controversial ideas and unpleasant arguments in the public sphere were tracked. The level of hostility was measured through online discussions using a Deep Learning (DL)-based classifier. Natural Language Processing (NLP) and Markov models have been used to characterize the mood of the general populace. The results and applications of Artificial Intelligence (AI) to identify citizens' emotional pulses could enhance security, communication, and policymaking.