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All Journal International Journal of Electrical and Computer Engineering Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan Indonesian Journal of History Education JIPF (Jurnal Ilmu Pendidikan Fisika) Jurnal Pendidikan Matematika (Kudus) Jurnal Tarbiyah : Jurnal Ilmiah Kependidikan Edu Sportivo: Indonesian Journal of Physical Education INSECTA: Integrative Science Education and Teaching Activity Journal Journal of Information Systems and Technology Research Analisa: Journal of Social Science and Religion Buletin Edukasi Indonesia Bigint Computing Journal
Karimi, Amir
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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Journal : Journal of Information Systems and Technology Research

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Deep Learning-Based Sentiment and Emotion Analysis of Social Media Data to Identify Factors Affecting Healthy Food Choices in Urban Communities Rasyid, Rachmat; Rafli R, Muh; Faisal, Faisal; Suherwin, Suherwin; Asia, Siti Nur; Karimi, Amir
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1288

Abstract

The increasing influence of social media on public perception has made it a powerful driver of dietary behavior in urban communities. Nevertheless, the abundance of unverified health information often obscures individuals’ ability to make informed food choices. This study proposes a deep learning-based framework to analyze sentiment and emotion from social media discourse in order to uncover the key factors affecting healthy food decisions in urban settings. By applying Natural Language Processing (NLP) techniques and advanced deep learning models to a large corpus of user-generated content, the research identifies significant patterns linking emotional expression with food-related decision-making. The results indicate that positive emotions, such as pride and satisfaction, are strongly associated with healthy food promotion, while negative emotions, including frustration, are predominantly tied to affordability, accessibility, and convenience issues. Among these, price and food quality emerge as the most critical determinants shaping consumer preferences. These findings underscore the importance of integrating emotional and socio-economic considerations into public health strategies. Beyond offering empirical insights, this study demonstrates the scalability and effectiveness of deep learning in extracting nuanced perspectives from unstructured social media data, thereby contributing a robust methodological approach for real-time public health monitoring and intervention design.  
Co-Authors Abdullah, Khairul Hafezad Adi Rahmat Ahmad Yusuf Antonio Constantino Soares Arcelus-Ulibarrena, Juana Maria Arif Purnomo Asia, Siti Nur Bjelica, Bojan Entas, Derinta Fadhila, Qonita Faisal Faisal Febri Prasetya Fortuna, Aprilla Fredyarini Soedjiwo, Novena Ade Fredyarini Soedjiwo, Novena Ade Ganda Febri Kurniawan Gandomani, Taghi Javdani García, Juan Luis Cabanillas Guidi, Elisa Hutagalung, Jennie Febrina Mardianti, Fani Mrs Yanti Hamdiyati Muslim Muslim Nagoor Meera Abdullah Nanang Winarno Parlindungan Sinaga Perdima, Feby Elra Putra, Bima Maulana Quintero, Armando Monterrosa Rafli R, Muh Rahma, Aulia Eka Rasyid, Rachmat Romadi Romadi Salman, Amna Sari, Winda Purnama Sihombing, Rizky Agassy Sitanggang, Winanta Skrypchenko, Iryna Suherwin, Suherwin Suroyo Suroyo Veithzal Rivai Zainal Wahidin, Naufal Rabah Wandi, Wandi Winny Liliawati Yassin, Abdulnassir Yuli Haryanto, Yuli