Sentiment Analysis and Opinion Mining

Latest papers

• Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions

  Aditya Agrawal, Alwarappan Nakkiran, Darshan Fofadiya, Alex Karlsson, Harsha Aduri · 5 June 2026

  This position paper argues that Retrieval-Augmented Generation systems exhibit a systematic factual bias-optimizing for epistemic uncertainty reduction while ignoring the aleatoric uncertainty inherent in opinion-rich content - and that this misalignment demands a paradigm shift in retrieval system …

• IdiomX A Multilingual Benchmark for Idiom Understanding, Retrieval, and Interpretation

  Ayman Ali Sharara · 3 June 2026

  Idiomatic expressions remain a persistent challenge for natural language processing because their meanings are often non-compositional, context-dependent, and difficult to align across languages. Existing idiom resources are often limited in scale, contextual diversity, or multilingual coverage, res…

• Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detection

  Pritam Kadasi, Anuj Tiwari, Mayank Singh · 3 June 2026

  Our submission presented in this paper is for SemEval-2026 Task 9: Multilingual Text Classification Challenge - Polarization Detection and it covers all three subtasks: (1) binary polarization detection, (2) polarization type classification and (3) polarization manifestation identification. We adopt…

• DiffuSent: Towards a Unified Diffusion Framework for Aspect-Based Sentiment Analysis

  Shu Long, Yanglei Gan, Xuchuan Zhou · 2 June 2026

  Aspect-Based Sentiment Analysis (ABSA) encompasses seven distinct subtasks, each focusing on different extracted elements. Despite the proven success of generative models in unified aspect sentiment analysis, existing approaches often rely on auto-regressive token-by-token generation without graspin…

• SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector

  Dineth Jayakody, Pasindu Thenahandi, Sampath Jayarathna · 2 June 2026

  Online travel platforms generate vast volumes of user-generated hotel reviews, offering rich opportunities to understand traveler experiences at scale. However, transforming unstructured textual feedback into structured, actionable insights remains a challenging task. This paper presents SentimentLe…

• Fine-grained Verification via Diagnostic Reasoning Supervision for Aspect Sentiment Triplet Extraction

  Wenna Lai, Haoran Xie, Guandong Xu, Qing Li, S. Joe Qin · 1 June 2026

  Aspect Sentiment Triplet Extraction (ASTE) aims to identify aspect terms, opinion terms, and sentiment polarities as structured triplets, providing essential inputs for downstream information system applications such as opinion mining, explainable recommendations, and review summarization. Prior wor…

• When Models Disagree: Rethinking LLM Evaluation for Public Comment Analysis

  Aisha Najera, Alvin Moon, Vedant Srinivasan, Rajesh Veeraraghavan · 29 May 2026

  Federal agencies are deploying large language models (LLMs) to categorize public comment corpora, where the model's organization of the record shapes what policymakers see and which arguments register. Standard evaluation, anchored on stance accuracy against a small validated set, cannot detect when…

• Faithfulness Evaluation for Decoder-only LLM Attributions with Controlled Retained Information

  Xin Huang, Antoni B. Chan · 27 May 2026

  Large Language Models (LLMs) are increasingly evaluated with input attribution methods, yet comparing such explanations remains challenging. Existing soft-perturbation faithfulness metrics, such as Soft-NC and Soft-NS, can conflate attribution quality with the number of words retained during perturb…

• StakeBench: Evaluating Language Understanding Grounded in Market Commitment

  Yunhua Pei, Jingyu Hu, Yiwei Shi, Hongnan Ma, Weiru Liu, John Cartlidge · 26 May 2026

  Existing financial NLP benchmarks often rely on labels supplied by outside observers, measuring how language is perceived rather than what speakers have committed to in the market. We introduce StakeBench, an evaluation framework for language understanding grounded in market commitment. StakeBench l…

• Uncertainty Decomposition via Cyclical SG-MCMC and Soft-label Learning for Subjective NLP

  Keito Inoshita, Takato Ueno · 26 May 2026

  Annotator disagreement in emotion classification reflects ambiguity intrinsic to emotion concepts and is essential for predictor-quality assessment in subjective NLP. Yet no prior work integrates soft-label learning with Bayesian deep learning to evaluate uncertainty along axes including annotator-d…

• A Controlled Synthetic Benchmark for Educational Aspect-Based Sentiment Analysis

  Yehudit Aperstein, Alexander Apartsin · 26 May 2026

  Educational aspect-based sentiment analysis (ABSA) can support course improvement, but public aspect-labeled student feedback remains scarce because educational reviews are private, institution-specific, and expensive to annotate. This study introduces a controlled synthetic benchmark for educationa…

• More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts

  V\'ictor Yeste, Paolo Rosso · 25 May 2026

  Detecting Schwartz values in political text is difficult because implicit cues often depend on surrounding arguments and fine-grained distinctions between neighboring values. We study when context and explicit moral knowledge help sentence-level value detection. Using the ValuesML/Touch\'e ValueEval…

• Interpretable Discriminative Text Representations via Agreement and Label Disentanglement

  Tong Wang, Yiqing Xu, Leo Yang Yang · 22 May 2026

  Interpretable text representations should expose coordinates that are not only predictive, but also meaningful enough for independent auditors to apply. Existing discriminative representations often use anonymous embedding directions, while concept-bottleneck and LLM-assisted methods attach natural-…

• Single-Pass, Depth-Selective Reading for Multi-Aspect Sentiment Analysis

  Yan Xia, Zhuangzhuang Pan, Amirrudin Kamsin, Chee Seng Chan · 22 May 2026

  Aspect-Term Sentiment Analysis (ATSA) in multi-aspect sentences faces a fundamental tradeoff between efficiency and expressiveness. Existing models either re-encode the sentence for each aspect or rely on static use of deep representations, leading to redundant computation and limited adaptivity. We…

• Compositional Literary Primitives in Instruction-Tuned LLMs: Cross-Architectural SAE Features for Self, Style, and Affect

  Joao Paulo Cavalcante Presa, Savio Salvarino Teles de Oliveira · 20 May 2026

  We characterize a compositional architecture of literary primitives in two instruction-tuned large language models (Llama 3.1 8B-Instruct and Gemma 2 9B-IT) via sparse autoencoders on mid-depth residual streams. Four feature classes emerge: naming-gates that promote lexical tokens of a target affect…

• Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench

  Tianyu Wang, Jiajun Li, Jianghao Lin · 19 May 2026

  LLMs are increasingly used as ``digital consumers'' to simulate public opinion, pre-test marketing decisions, and anticipate audience response. However, existing evaluations rarely ask whether a model can reconstruct the concrete reaction patterns that real consumers surface in public discourse. We …

• A Hormone-inspired Emotion Layer for Transformer language models (HELT)

  Eslam Reda, Sara El-Metwally · 15 May 2026

  Large Language Models have demonstrated remarkable capabilities in generating contextually relevant and grammatically correct text. However, they fundamentally lack the ability to process and respond to emotional context in a manner analogous to human emotional cognition. Current approaches to emoti…

• PERCEIVE: A Benchmark for Personalized Emotion and Communication Behavior Understanding on Social Media

  Jian Liao, Yujin Zheng, Suge Wang, Jianxing Zheng, Deyu Li · 14 May 2026

  Current emotion analysis in social media is predominantly author-centric, failing to capture the subjective nature of emotional responses across diverse readers. This paradigm overlooks the crucial link between individual perception, communication behavior, and the underlying social network. To brid…

• SSP-based construction of evaluation-annotated data for fine-grained aspect-based sentiment analysis

  Suwon Choi, Shinwoo Kim, Changhoe Hwang, Gwanghoon Yoo, Eric Laporte, Jeesun Nam · 11 May 2026

  We report the construction of a Korean evaluation-annotated corpus, hereafter called 'Evaluation Annotated Dataset (EVAD)', and its use in Aspect-Based Sentiment Analysis (ABSA) extended in order to cover e-commerce reviews containing sentiment and non-sentiment linguistic patterns. The annotation p…

• PREFER: Personalized Review Summarization with Online Preference Learning

  Millend Roy, Agostino Capponi, Vineet Goyal · 8 May 2026

  Product reviews significantly influence purchasing decisions on e-commerce platforms. However, the sheer volume of reviews can overwhelm users, obscuring the information most relevant to their specific needs. Current e-commerce summarization systems typically produce generic, static summaries that f…

• TCDA: Thread-Constrained Discourse-Aware Modeling for Conversational Sentiment Quadruple Analysis

  Xinran Li, Xinze Che, Yifan Lyu, Zhiqi Huang, Xiujuan Xu · 6 May 2026

  Conversational Aspect-based Sentiment Quadruple Analysis (DiaASQ) needs to capture the complex interrelationships in multiple rounds of dialogues. Existing methods usually employ simple Graph Convolutional Networks (GCN), which introduce structural noise and fail to consider the temporal sequence of…

• Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification

  Shubham Harkare, Arvind Yogesh Suresh Babu, Yash Kulkarni · 6 May 2026

  While pre-trained Transformer models achieve high accuracy on in-domain sentiment classification, they frequently experience severe performance degradation when transferring to out-of-domain data. We hypothesize that this generalization gap is driven by reliance on domain-specific spurious tokens. A…

• PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention

  Maoheng Li, Ling Zhou, Xiaohua Huang, Rubing Huang, Wenming Zheng, Guoying Zhao · 6 May 2026

  Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial attention in multimodal understanding. Recent advancements have predominantly relied on na\"{\i}ve similarity-based attention mechanisms and uniform …

• Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews

  Kartikey Singh Bhandari, Tanish Jain, Archit Agrawal, Dhruv Kumar, Praveen Kumar, Pratik Narang · 6 May 2026

  Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommendations remains difficult. Standard sentiment/aspect analysis is largely descriptive, while direct prompting of large language models (LLMs) often yields generi…

• Beyond Semantics: Measuring Fine-Grained Emotion Preservation in Small Language Model-Based Machine Translation

  Dawid Wisniewski, Igor Czudy · 1 May 2026

  Preserving affective nuance remains a challenge in Machine Translation (MT), where semantic equivalence often takes precedence over emotional fidelity. This paper evaluates the performance of three state-of-the-art Small Language Models (SLMs) -- EuroLLM, Aya Expanse, and Gemma -- in maintaining fin…