Textual Taste Buds: A Profound Exploration of Emotion Identification in Food Recipes through BERT and AttBiRNN Models

Textual Taste Buds: A Profound Exploration of Emotion Identification in Food Recipes through BERT and AttBiRNN Models

Registration ID: IJNRD_206484

Published ID: IJNRD2310077

DOI: Click Here to Get

Amir Ali , Stanisław Matuszewski , Jacek Czupyt , Usman Ahmad

Food Review, Deep Learning, Sentiment Analysis, BERT

Sentiment analysis of food reviews has become increasingly vital in understanding customer preferences and enhancing the food and hospitality industry's offerings. However, conducting precise sentiment analysis in this context, particularly with five distinct sentiment classes (very negative, negative, neutral, positive, and very positive), poses significant challenges. This paper addresses these challenges by proposing an advanced approach for five-class sentiment analysis. Leveraging state-of-the-art natural language processing techniques, we explored various models, including RNN, BiRNN, AttBiRNN, and BERT. Our results indicate that BERT, with its bidirectional contextual understanding, outperformed the other models, achieving the highest accuracy and F1 score. AttBiRNN also demonstrated strong performance. This research contributes to the field of sentiment analysis, providing valuable insights into customer sentiments within the food and hospitality industry and emphasizing the efficacy of advanced models like BERT for fine-grained analysis.

Published Paper   E-Certificate

"Textual Taste Buds: A Profound Exploration of Emotion Identification in Food Recipes through BERT and AttBiRNN Models", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 10, page no.a690-a694, October-2023, Available :https://ijnrd.org/papers/IJNRD2310077.pdf

Volume 8 Issue 10, October-2023

Pages : a690-a694

Paper Reg. ID: IJNRD_206484

Published Paper Id: IJNRD2310077

Downloads: 000121192

Research Area: Computer Science & Technology 

Country: Warsaw, Mazowiecka, Poland

Published Paper PDF: https://ijnrd.org/papers/IJNRD2310077.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2310077

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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