Sentiment Analysis
Sentiment analysis aims to automatically determine the emotional tone expressed in text, aiming to understand opinions and attitudes. Current research heavily focuses on leveraging large language models (LLMs) like BERT and its variants, along with other architectures such as graph neural networks, to improve accuracy and efficiency, particularly in multimodal settings and low-resource languages. This field is crucial for various applications, including market research, social media monitoring, and understanding public opinion, driving advancements in natural language processing and impacting decision-making across numerous sectors.
Papers
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition
Shahin Amiriparian, Lukas Christ, Alexander Kathan, Maurice Gerczuk, Niklas Müller, Steffen Klug, Lukas Stappen, Andreas König, Erik Cambria, Björn Schuller, Simone Eulitz
A Labelled Dataset for Sentiment Analysis of Videos on YouTube, TikTok, and Other Sources about the 2024 Outbreak of Measles
Nirmalya Thakur, Vanessa Su, Mingchen Shao, Kesha A. Patel, Hongseok Jeong, Victoria Knieling, Andrew Bian
COVID-19 Twitter Sentiment Classification Using Hybrid Deep Learning Model Based on Grid Search Methodology
Jitendra Tembhurne, Anant Agrawal, Kirtan Lakhotia
Why is "Problems" Predictive of Positive Sentiment? A Case Study of Explaining Unintuitive Features in Sentiment Classification
Jiaming Qu, Jaime Arguello, Yue Wang
Evaluation of data inconsistency for multi-modal sentiment analysis
Yufei Wang, Mengyue Wu
Improving In-Context Learning with Prediction Feedback for Sentiment Analysis
Hongling Xu, Qianlong Wang, Yice Zhang, Min Yang, Xi Zeng, Bing Qin, Ruifeng Xu
RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis
Md. Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe, Md. Ashad Alam
Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios
Millicent Ochieng, Varun Gumma, Sunayana Sitaram, Jindong Wang, Vishrav Chaudhary, Keshet Ronen, Kalika Bali, Jacki O'Neill
Are PPO-ed Language Models Hackable?
Suraj Anand, David Getzen
Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions
Neha Sharma, Kairit Sirts
PRFashion24: A Dataset for Sentiment Analysis of Fashion Products Reviews in Persian
Mehrimah Amirpour, Reza Azmi
Instruction Tuning with Retrieval-based Examples Ranking for Aspect-based Sentiment Analysis
Guangmin Zheng, Jin Wang, Liang-Chih Yu, Xuejie Zhang