Aspect-Based Sentiment Analysis

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Aspect-Based Sentiment Analysis studies how to find opinion targets—such as food, service, or battery life—and link them to sentiment, opinion terms, or explanations. Common tasks include aspect and opinion span extraction, triplet and quadruple prediction, implicit aspect identification, and valence-arousal scoring. Methods range from fine-tuned Transformer encoders, sequence labeling, and syntax or graph models to prompted or fine-tuned large language models, often supported by synthetic data, verification, or distillation. A central challenge is making structured predictions reliable across domains and languages while reducing annotation and inference costs, especially where labeled data are scarce.

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52 papers4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Zero-Shot to Full-Resource: Cross-lingual Transfer Strategies for Aspect-Based Sentiment Analysis
Apr 29, 2026Jakob Fehle, Nils Constantin Hellwig, Udo Kruschwitz +1Multilingual Language Model Evaluation Aspect-Based Sentiment Analysis
Media Informatics Group, University of Regensburg, Regensburg, Germany · Information Science Group, University of Regensburg, Regensburg, Germany
$\mathcal{S}^2$ IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction
Apr 25, 2026Bingfeng Chen, Chenjie Qiu, Yifeng Xie +3LLM Fine-Tuning Aspect-Based Sentiment Analysis
School of Computer Science, Guangdong University of Technology · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) · Peng Cheng Laboratory +1
From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning
Apr 15, 2026Shihao Zhang, Ziwei Wang, Jie Zhou +6Aspect-Based Sentiment Analysis RL for Language Model Reasoning
School of Computer Science and Technology, East China Normal University · Shanghai Qiji Zhifeng Co., Ltd. · Ocean University of China
LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset
Apr 12, 2026Aizihaierjiang Yusufu, Jiang Liu, Kamran Aziz +5Aspect-Based Sentiment Analysis Low-Resource Language Processing
Xinjiang Engineering Technology Research Center for Smart Education and Application, School of Computer Science and Technology, Xinjiang Normal University, Urumqi, 830054, Xinjiang, China. · Key Laboratory of Aerospace Information Security and Trusted Computing, School of Cyber Science and Engineering, Wuhan University, Wuhan, 430000,Hubei, China. · Hainan Bielefeld University of Applied Sciences, Central Avenue and East 13, Danzhou, 578001, Hainan, China. +1
Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction
Apr 10, 2026Zongming Cai, Jianhang Tang, Zhenyong Zhang +3Aspect-Based Sentiment Analysis Federated Learning
State Key Laboratory of Public Big Data, Guizhou University · College of Computer Science and Technology, Guizhou University · School of Information Engineering, Guangdong University of Technology +1
NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment Regression
Apr 10, 2026Tong Wu, Nicolay Rusnachenko, Huizhi LiangMultilingual Sentiment Analysis Sentiment Analysis
Independent Researcher · Centre for Applied Creative Technologies (CFACT+), Bournemouth University, UK · School of Computing, Newcastle University, Newcastle upon Tyne, UK
SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)
Apr 8, 2026Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14Sentiment Analysis Aspect-Based Sentiment Analysis
Yuan Ze University · University of Göttingen · Imperial College London +10
Beyond Cosine Similarity: Zero-Initialized Residual Complex Projection for Aspect-Based Sentiment Analysis
Mar 30, 2026Yijin Wang, Fandi Sun, Haoyu WenAspect-Based Sentiment Analysis Representation Learning
School of Economics and Management, Xidian University, Xi’an, China
Approaches to Analysing Historical Newspapers Using LLMs
Mar 26, 2026Filip Dobranić, Tina Munda, Oliver Pejić +8Historical Document Analysis Political Discourse Analysis
Institute of Contemporary History, Privoz 11, SI-1000 Ljubljana · Faculty of Arts, University of Ljubljana, Aškerčeva 2, SI-1000 Ljubljana · Faculty of Computer Science, University of Ljubljana, Večna pot 113, SI-1000 Ljubljana
LogSigma at SemEval-2026 Task 3: Uncertainty-Weighted Multitask Learning for Dimensional Aspect-Based Sentiment Analysis
Mar 26, 2026Baraa Hikal, Jonas Becker, Bela GippMultilingual Sentiment Analysis Sentiment Analysis
University of Göttingen, Germany · LKA NRW, Germany
Beyond Correlation: Refutation-Validated Aspect-Based Sentiment Analysis for Explainable Energy Market Returns
Mar 23, 2026Wihan van der Heever, Keane Ong, Ranjan Satapathy +1Financial Sentiment Analysis Aspect-Based Sentiment Analysis
College of Computing and Data Science, Nanyang Technological University, 50 Nanyang Ave, Singapore, 639798, Singapore · College of Design and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore, 117575, Singapore · Institute of High Performance Computing, Agency for Science, Technology and Research, Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Singapore
DanceHA: A Multi-Agent Framework for Document-Level Aspect-Based Sentiment Analysis
Mar 17, 2026Lei Wang, Min Huang, Eduard DragutAspect-Based Sentiment Analysis Multi-Agent Systems
Temple University, Philadelphia, PA, USA · Independent Researcher, Philadelphia, PA, USA
Generate Then Correct: Single Shot Global Correction for Aspect Sentiment Quad Prediction
Mar 14, 2026Shidong He, Haoyu Wang, Wenjie LuoExposure Bias Aspect-Based Sentiment Analysis
School of Cyber Security and Computer, Hebei University, Baoding, China. · Faculty of Computer Science, Dalhousie University, Halifax, Canada.
LLM-Augmented Therapy Normalization and Aspect-Based Sentiment Analysis for Treatment-Resistant Depression on Reddit
Mar 12, 2026Yuxin Zhu, Sahithi Lakamana, Masoud Rouhizadeh +3Mental Health Sentiment Analysis
Department of Biomedical Informatics, Emory University, Atlanta, GA · Department of Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, FL
QuadAI at SemEval-2026 Task 3: Ensemble Learning of Hybrid RoBERTa and LLMs for Dimensional Aspect-Based Sentiment Analysis
Mar 8, 2026A. J. W. de Vink, Filippos Karolos Ventirozos, Natalia Amat-Lefort +1Aspect-Based Sentiment Analysis Language Model Ensembles
LIACS, Leiden University, NL · Manchester Metropolitan University, UK · Leiden University Medical Center, NL
AILS-NTUA at SemEval-2026 Task 3: Efficient Dimensional Aspect-Based Sentiment Analysis
Mar 5, 2026Stavros Gazetas, Giorgos Filandrianos, Maria Lymperaiou +3Aspect-Based Sentiment Analysis
School of Electrical and Computer Engineering, AILS Laboratory National Technical University of Athens
nchellwig at SemEval-2026 Task 3: Self-Consistent Structured Generation (SCSG) for Dimensional Aspect-Based Sentiment Analysis using Large Language Models
Mar 2, 2026Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1Aspect-Based Sentiment Analysis Structured Output Generation
Media Informatics Group, University of Regensburg, Regensburg, Germany · Information Science Group, University of Regensburg, Regensburg, Germany
LLM-as-an-Annotator: Training Lightweight Models with LLM-Annotated Examples for Aspect Sentiment Tuple Prediction
Mar 2, 2026Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1Aspect-Based Sentiment Analysis LLM-Assisted Annotation
Media Informatics Group, University of Regensburg, Regensburg, Germany · Information Science Group, University of Regensburg, Regensburg, Germany
AnnoABSA: A Web-Based Annotation Tool for Aspect-Based Sentiment Analysis with Retrieval-Augmented Suggestions
Mar 2, 2026Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1Aspect-Based Sentiment Analysis LLM-Assisted Annotation
Media Informatics Group, University of Regensburg, Regensburg, Germany · Information Science Group, University of Regensburg, Regensburg, Germany
Extending Czech Aspect-Based Sentiment Analysis with Opinion Terms: Dataset and LLM Benchmarks
Feb 26, 2026Jakub Šmíd, Pavel Přibáň, Pavel KrálAspect-Based Sentiment Analysis Low-Resource Language Processing
Department of Computer Science and Engineering, University of West Bohemia in Pilsen, Faculty of Applied Sciences, Univerzitní 2732/8, 301 00 Pilsen, Czech Republic · NTIS – New Technologies for the Information Society, University of West Bohemia in Pilsen, Faculty of Applied Sciences, Univerzitní 2732/8, 301 00 Pilsen, Czech Republic
Beyond the Star Rating: A Scalable Framework for Aspect-Based Sentiment Analysis Using LLMs and Text Classification
Feb 24, 2026Vishal Patil, Shree Vaishnavi Bacha, Revanth Yamani +2Aspect-Based Sentiment Analysis Document Information Extraction
University of Southern California, Marina del Rey, 90292, CA, USA.
Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
Feb 18, 2026Mohammad H. A. Monfared, Lucie Flek, Akbar KarimiSynthetic Data Augmentation Large Language Model-Based Data Augmentation
Bonn-Aachen International Center for Information Technology, University of Bonn, Germany · Lamarr Institute for Machine Learning and Artificial Intelligence, Germany

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Zero-Shot to Full-Resource: Cross-lingual Transfer Strategies for Aspect-Based Sentiment Analysis

Jakob Fehle, Nils Constantin Hellwig, Udo Kruschwitz, Christian Wolff

Media Informatics Group, University of Regensburg, Regensburg, Germany · Information Science Group, University of Regensburg, Regensburg, Germany

Multilingual Language Model Evaluation Aspect-Based Sentiment Analysis Cross-Lingual Transfer Multilingual Sentiment Analysis

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Aspect-based Sentiment Analysis (ABSA) extracts fine-grained opinions toward specific aspects within text but remains largely English-focused despite major advances in transformer-based and instruction-tuned models. This work presents a multilingual evaluation of state-of-the-art ABSA approaches across seven languages (English, German, French, Dutch, Russian, Spanish, and Czech) and four subtasks (ACD, ACSA, TASD, ASQP). We systematically compare different transformer architectures under zero-resource, data-only, and full-resource settings, using cross-lingual transfer, code-switching and machine translation. Fine-tuned Large Language Models (LLMs) achieve the highest overall scores, particularly in complex generative tasks, while few-shot counterparts approach this performance in simpler setups, where smaller encoder models also remain competitive. Cross-lingual training on multiple non-target languages yields the strongest transfer for fine-tuned LLMs, while smaller encoder or seq-to-seq models benefit most from code-switching, highlighting architecture-specific strategies for multilingual ABSA. We further contribute two new German datasets, an adapted GERestaurant and the first German ASQP dataset (GERest), to encourage multilingual ABSA research beyond English.