Large language models (LLMs) are supposed to acquire unconscious human knowledge and feelings, such as social common sense and biases, by training models from large amounts of text. However, it is not clear how much the sentiments of specific social groups can be captured in various LLMs. In this study, we focus on social groups defined in terms of nationality, religion, and race/ethnicity, and validate the extent to which sentiments between social groups can be captured in and extracted from LLMs. Specifically, we input questions regarding sentiments from one group to another into LLMs, apply sentiment analysis to the responses, and compare the results with social surveys. The validation results using five representative LLMs showed higher correlations with relatively small p-values for nationalities and religions, whose number of data points were relatively large. This result indicates that the LLM responses including the inter-group sentiments align well with actual social survey results.
AI in Mental Health: Emotional and Sentiment Analysis of Large Language Models' Responses to Depression, Anxiety, and Stress Queries
University of Tehran（塔里斯坦大学）；University of South Carolina（南卡罗来纳大学）；University of West London（西伦敦大学）；Azad University（阿扎德大学）；Amirkabir University of Technology（阿米卡比尔技术大学）
How Quantization Shapes Bias in Large Language Models
Tsinghua University（清华大学）；The Hebrew University of Jerusalem（耶路撒冷希伯来大学）；TU Darmstadt（达姆施塔特工业大学）；National Research Center for Applied Cybersecurity ATHENE（雅典娜国家应用网络安全研究中心）
Automatic Classifiers Underdetect Emotions Expressed by Men
University of Technology Sydney（技术大学悉尼大学）；University of Konstanz（康斯坦茨大学）；Medical University of Vienna（维也纳医学院）；University of Ulm（乌尔姆大学）；Complexity Science Hub（复杂科学中心）
Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?
International Digital Economy Academy (IDEA)（国际数字经济学院（IDEA））；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Data Science and Analytics Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）数据科学与分析学域）；Financial Technology Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）金融科技学域）
Listwise Preference Optimization with Element-wise Confusions for Aspect Sentiment Quad Prediction
The Hong Kong Polytechnic University（香港理工大学）；Lingnan University（岭大）；University of Technology Sydney（悉尼大学）；The Education University of Hong Kong（香港教育大学）
Beyond classical and contemporary models: a transformative AI framework for student dropout prediction in distance learning using RAG, Prompt engineering, and Cross-modal fusion
Consistency Analysis of Sentiment Predictions using Syntactic & Semantic Context Assessment Summarization (SSAS)
Tellagence Inc.（Tellagence公司）；Villanova School of Business, Villanova University（维拉文纳大学商学院）；Maseeh College of Engineering and Computer Science, Portland State University（波特兰州立大学Maseeh工程与计算机科学学院）
C2F-Thinker: Coarse-to-Fine Reasoning with Hint-Guided Reinforcement Learning for Multimodal Sentiment Analysis
School of Computer Science, South China Normal University（华南师范大学计算机科学学院）；School of Electronic and Information Engineering, South China University of Technology（华南理工大学电子与信息工程学院）
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models
Chinese University of Hong Kong（香港中文大学）；Peking University（北京大学）；National University of Singapore（新加坡国立大学）；Microsoft Research（微软研究院）；IBM Research（IBM研究院）
A Survey of Quantum-Cognitively Inspired Sentiment Analysis Models
Beijing Institute of Technology（北京理工大学）；University of Copenhagen（哥本哈根大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Zhengzhou University of Light Industry（郑州轻工业大学）；The Open University（开放大学）
BTC-SAM: Leveraging LLMs for Generation of Bias Test Cases for Sentiment Analysis Models
Insight SFI Research Center on Data Analytics, Dublin City University（数据分析洞察SFI研究中心，都柏林城市大学）；Laboratoire LITAN, École supérieure en Sciences et Technologies de l’Informatique et du Numérique（LITAN实验室，信息与数字技术高等学院）；School of Computing, Dublin City University（计算学院，都柏林城市大学）；Plus Que Pro, Strasbourg, France（斯特拉斯堡法国Plus Que Pro公司）；ServiceNow, Zurich, Switzerland（瑞士苏黎世ServiceNow公司）；Department of Information Engineering and Computer Science, University of Trento（信息工程与计算机科学系，特伦托大学）；Télécom SudParis, SAMOVAR, Institut Polytechnique de Paris（巴黎理工学院SAMOVAR，Telecom SudParis）
