sc 21(13): e4

Research Article

Application of Sentiment Analysis in Understanding Human Emotions and Behaviour

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  • @ARTICLE{10.4108/eai.6-10-2020.166547,
        author={Sweta Saraff and Roman Taraban and Rishipal Rishipal and Ramakrishna Biswal and Shweta Kedas and Shakuntala Gupta},
        title={Application of Sentiment Analysis in Understanding Human Emotions and Behaviour},
        journal={EAI Endorsed Transactions on Smart Cities},
        keywords={Sentiment Analysis, Human Behavior, Emotions, Natural Language Processing},
  • Sweta Saraff
    Roman Taraban
    Rishipal Rishipal
    Ramakrishna Biswal
    Shweta Kedas
    Shakuntala Gupta
    Year: 2020
    Application of Sentiment Analysis in Understanding Human Emotions and Behaviour
    DOI: 10.4108/eai.6-10-2020.166547
Sweta Saraff1,*, Roman Taraban2, Rishipal Rishipal3, Ramakrishna Biswal4, Shweta Kedas5, Shakuntala Gupta4
  • 1: Amity Institute of Psychology and Allied Sciences, Amity University, Kolkata, India
  • 2: Department of Psychological Sciences, Texas Tech University, USA
  • 3: Humanities & Applied Sciences, S, Haryana, India
  • 4: Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, India
  • 5: Department of Computer Science, National Institute of Technology, Rourkela, India
*Contact email:


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.