INTRODUCTION: Presently, naturalistic observation is considered as critical in understanding, and predicting the complexities of feelings and sentiments. Emerging trends of social media has ...completely revolutionized the process of communication. Social media, microblogging, and other means of e-communication can be used for extracting the content to decode the quality, valence, and effectiveness of communication. OBJECTIVES: In this paper, we represent the explanatory urge of mental health assessment during a pandemic situation, especially in a smart city scenario. METHODS: We reviewed the role of sentimental analysis, as an emerging application tool for emotional and behavioural analysis for the population affected by a pandemic. This paper examines the prospect of analysing the sentiments through machine learning tools to understand, describe, and predict human behavior. CONCLUSION: Further analysis of this psychological e-content can be used to understand and predict the patterns of human sentiments.
Reading paragraphs, understanding the related questions and answering them has always been a difficult task for the machines. Humans have the capability to understand the logic and meaning of a ...question and answer it to maintain a proper mode of interaction. But for machines, this is a complex task. The main focus of this research work is to explore the various machine learning and neural networks based techniques to develop and train a model on context of paragraphs related questions and answers and then test the model on an user given paragraph and question. This paper presents a thorough understanding of data analysis of the SQuAD data set and word embedding applied on the questions and answers of training set of the SQuAD data set.
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