Paper Title
Emotion Detection in Text : A Deep Learning Approach for Sentiment Analysis
Article Identifiers
Authors
Prince Patel , Dhara Patel , Madhvi Bera
Keywords
Sentiment Analysis, BERT Model, Natural Language Processing, Emotion Detection, Text Classification, Social Media Analysis
Abstract
Emotion detection in text, a key part of sentiment analysis, plays a vital role in understanding human emotions and opinions expressed in diverse textual formats, such as social media posts, customer reviews, and chat interactions. Deep learning techniques have shown great promise in this field due to their ability to learn complex patterns from text data. This paper presents a comprehensive exploration of deep learning methodologies for emotion detection in text. We curate a carefully annotated dataset and use the advanced BERT architecture to build a robust emotion detection system. Our empirical findings demonstrate the effectiveness of our approach, revealing that it outperforms traditional machine learning methods. Additionally, we investigate the interpretability of the model's predictions, shedding light on the mechanisms that underpin emotion attribution to textual content. Our research contributes significantly to the field of natural language processing, advancing our understanding of emotion detection via deep learning and providing valuable tools for applications such as social media monitoring, customer feedback analysis, and mental health support.
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How To Cite (APA)
Prince Patel, Dhara Patel, & Madhvi Bera (October-2023). Emotion Detection in Text : A Deep Learning Approach for Sentiment Analysis. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(10), b506-b516. https://ijnrd.org/papers/IJNRD2310156.pdf
Issue
Volume 8 Issue 10, October-2023
Pages : b506-b516
Other Publication Details
Paper Reg. ID: IJNRD_206851
Published Paper Id: IJNRD2310156
Downloads: 000121995
Research Area: Computer Science & TechnologyÂ
Country: Ahmedabad, Gujarat, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2310156.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2310156
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.
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Paper Submission Open For: October 2025
Current Issue: Volume 10 | Issue 10 | October 2025
Impact Factor: 8.76
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