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Article
Computer Science, Artificial Intelligence
Carmen De Maio et al.
Summary: This paper discusses the lack of transparency in machine learning and deep learning models and proposes a new measure called Congruity to measure the reliability of model results. Experimental results show a high correlation between Congruity and accuracy.
NEURAL COMPUTING & APPLICATIONS
(2023)
Review
Environmental Studies
Hengyun Li et al.
Summary: This study investigates the impact of customer-generated content, specifically online reviews, on predicting restaurant survival using aspect-based sentiment analysis. The results show that aspect-based sentiment, focusing on specific factors like location, taste, price, service, and atmosphere, improves the accuracy of restaurant survival prediction compared to overall review sentiment. Additionally, the analysis of feature importance identifies which aspects of online reviews serve as optimal indicators for restaurant survival.
TOURISM MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Rui Mao et al.
Summary: With the breakthrough of large-scale pre-trained language model (PLM) technology, prompt-based classification tasks, such as sentiment analysis and emotion detection, have gained increasing attention. This study conducts a systematic empirical study on prompt-based sentiment analysis and emotion detection to investigate the biases of PLMs in affective computing.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Ahmed Samit Hatem et al.
Article
Multidisciplinary Sciences
Yu Liu et al.
Summary: This study explores the causes of inferiority feelings using social media data and finds that personal experience, social interaction, and love relationships are the main factors. These findings will help relevant institutions and organizations better understand individuals with inferiority feelings and develop targeted treatments for potential self-esteem problems.
SCIENTIFIC REPORTS
(2022)
Review
Computer Science, Artificial Intelligence
Yan Wang et al.
Summary: Affective computing combines emotion recognition and sentiment analysis, utilizing different types of data including physical information and physiological signals. This systematic review introduces emotion models, databases, and recent advances, aiming to help researchers understand the latest developments in this field.
INFORMATION FUSION
(2022)
Review
Computer Science, Information Systems
Pansy Nandwani et al.
Summary: Social networking platforms are essential for communicating feelings in the Internet era, with sentiment analysis helping to understand human psychology and emotion detection providing more precise insights into individual emotional/mental states.
SOCIAL NETWORK ANALYSIS AND MINING
(2021)
Review
Computer Science, Artificial Intelligence
Francisca Adoma Acheampong et al.
Summary: The importance of contextual information in NLP applications cannot be emphasized enough, with significant improvements observed in tasks like emotion recognition from texts. This paper discusses transformer-based models for NLP tasks, highlighting the pros and cons of models such as GPT, Transformer-XL, XLM, and BERT. Researchers have proposed various BERT-based models for text-based emotion detection due to BERT's strength and popularity in this field.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Review
Computer Science, Artificial Intelligence
Alexander Ligthart et al.
Summary: This paper presents the results of a tertiary study on sentiment analysis, providing a comprehensive overview of key topics, different approaches, challenges, and unresolved issues in the field. In addition, recent 112 deep learning-based sentiment analysis papers were identified and analyzed based on the deep learning algorithms used.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Marouane Birjali et al.
Summary: Sentiment analysis, also known as Opinion Mining, is the task of extracting and analyzing people's opinions and emotions towards different entities. It is a powerful tool used by businesses, governments, and researchers to gain insights and make better decisions. This paper provides a comprehensive study of sentiment analysis methods, challenges, and trends for researchers in the field.
KNOWLEDGE-BASED SYSTEMS
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Samira Zad et al.
Summary: Text-Based Emotion Detection is a rapidly growing field in Natural Language Processing that automates the extraction of emotions using machine learning. It has a wide range of applications in artificial intelligence, such as semantic analysis, historical corpus analysis, and product review studies.
2021 IEEE WORLD AI IOT CONGRESS (AIIOT)
(2021)
Article
Computer Science, Artificial Intelligence
Sheetal Kusal et al.
Summary: Online Social Media (OSM) like Facebook and Twitter has become a powerful tool to express people's opinions and feelings about current events through text. Text-based emotion detection using AI in social media big data is an emerging area of Natural Language Processing research, with applications in various fields. This study reviewed 827 Scopus and 83 Web of Science research papers from 2005-2020, analyzing different emotion models, datasets, algorithms, and application domains, as well as presenting quantitative details on publications, co-authorship networks, citation analysis, and research distribution. Challenges and potential solutions were also discussed for future research directions.
BIG DATA AND COGNITIVE COMPUTING
(2021)
Article
Multidisciplinary Sciences
Eric Mayor et al.
Summary: Research on temporal trajectories of emotions shared on Twitter shows that positive and negative emotions follow nonlinear circadian and circaseptan patterns. Self-referential content is more relevant to individuals. Emotional expression in emojis sometimes diverges from textual analysis, indicating some complementarity.
ROYAL SOCIETY OPEN SCIENCE
(2021)
Review
Computer Science, Artificial Intelligence
Nikhil Kumar Singh et al.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2020)
Review
Computer Science, Information Systems
Akshi Kumar et al.
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Ramesh Wadawadagi et al.
ARTIFICIAL INTELLIGENCE REVIEW
(2020)
Article
Computer Science, Artificial Intelligence
Nourah Alswaidan et al.
KNOWLEDGE AND INFORMATION SYSTEMS
(2020)
Review
Engineering, Multidisciplinary
Yuan JianHua et al.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2020)
Review
Computer Science, Interdisciplinary Applications
Francisca Adoma Acheampong et al.
ENGINEERING REPORTS
(2020)
Article
Computer Science, Information Systems
Alhassan Mabrouk et al.
Article
Education & Educational Research
Omar Y. Adwan et al.
INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING
(2020)
Review
Computer Science, Artificial Intelligence
Lei Zhang et al.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
(2018)
Correction
Neurosciences
Lisa Feldman Barrett
SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE
(2017)
Article
Computer Science, Artificial Intelligence
David Gomez et al.
NEURAL COMPUTATION
(2016)
Article
Computer Science, Artificial Intelligence
Shikha Jain et al.
JOURNAL OF INTELLIGENT SYSTEMS
(2015)
Review
Psychology
JA Russell
PSYCHOLOGICAL REVIEW
(2003)
