Emotions of students from online and offline texts

Document Type

Book Chapter

Publication Title

Computational Intelligence Applications for Text and Sentiment Data Analysis

Abstract

Students generally face tremendous pressure – from their competing peers, expectant guardians, and the society as a whole. These tend to make them vulnerable, and may lead to development of mental quirks that are very hard to remove with time. This chapter reports a venture to detect negative streaks existing within the human mind – especially, amongst the student community. Some machine-learning tools are utilized to study their sentiments from their day-to-day communications and practices. The end-product is a minuscule model to detect participants who are experiencing alarmingly stressed conditions. The system reports encouraging results within the limited periphery in which it has been tested so far. The main objective is to open up the vista of research on the virgin ground of detecting emotion from word usage and writing hand.

First Page

81

Last Page

111

DOI

10.1016/B978-0-32-390535-0.00009-4

Publication Date

1-1-2023

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