The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Real Time Emotion Recognition From Text Using Deep Learning and Data Analysis
|
|
Author(s): G. Sowmya (MLR Institute of Technology, India), Aurangabadkar Rohan (MLR Institute of Technology, India), Garikapati Kausthub Rao (MLR Institute of Technology, India), Koppolu Midhilesh (MLR Institute of Technology, India)and Atul kumar Nayak (MLR Institute of Technology, India)
Copyright: 2025
Pages: 14
Source title:
Humanizing Technology With Emotional Intelligence
Source Author(s)/Editor(s): Subrata Tikadar (Amity University, Kolkata, India), Haipeng Liu (Coventry University, UK), Pronaya Bhattacharya (Amity University Kolkata, India)and Samit Bhattacharya (Indian Institute of Technology Guwahati, India)
DOI: 10.4018/979-8-3693-7011-7.ch003
Purchase
|
Abstract
In the era of digital communication, understanding human emo- tions expressed through text has become increasingly vital, this increases the importance of accurate emotion recognition from text, which can be useful in various applications. This research paper delves into the realm of text-based emotion recognition precisely identifying and categorizing the emotions expressed in textual con- tent by using a deep learning approach such as Bi-LSTM. Presently, a significant portion of ongoing research primarily centers on the classification of text based on sentiments, with a small fraction focusing towards emotion recognition, particularly within the con- text of business applications. The principal objective of our research is to bridge the gap between the business organizations and the customers by analyzing the customer reviews based on emotion classification. This helps furnish organizations with a systematic approach to comprehend customer emotions, providing a more precise evaluation of product performance.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|