Latest Sentiment Analysis Research Papers
The newest Sentiment Analysis papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Sentiment Analysis so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.
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- Human-Based Machine Translation Evaluation: A Multi-Dimensional Approach to Sentiment, Emotion, and Argumentation Preservation in Chinese-English TranslationJingshi Zhou · University of Liverpool · Jan 1, 2028
The research landscape of Machine Translation Evaluation (MTE) has traditionally been dominated by automated metrics that, while computationally efficient, often fail to capture the nuanced aspects of translation quality paramount to human …
- Sentiment Analysis Performance of Lora-Enhanced Llm'sTunahan TİMUÇİN · Open MIND · Dec 11, 2026
On social media platforms, the increase in the number of users and the resulting increase in thedata produced by users have accelerated the prominence of some technologies. The most well-known of these areas is Natural Language Processing (…
- The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based MethodsIoanna Kaffeza, Efthymios Georgiou, Alexandros Potamianos · arXiv · Sep 10, 2026
Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods that promise more than they deliver. We provide three contributions: 1) a unified evaluat…
- Same Day, Same Story; One Day Ahead, a Different Signal: The Dual Validity of Financial SentimentAS Aravinthkakshan, Laven Srivastava, Harsh Nandwani · arXiv · Sep 10, 2026
Financial NLP has a standard workflow: validate a sentiment tool against human labels, then trust it to extract market signal. This assumes the two evaluations measure the same thing. We test that assumption in a setting where both can be m…
- Robust Multimodal Sentiment Analysis with Incomplete Modalities via Semantic-aware Completeness based ReconstructionHan-Jun Choi, Byunggill Joe, Saim Shin, Jin Yea Jang · arXiv · Sep 10, 2026
Recent multimodal sentiment analysis studies increasingly adopt text-centric fusion approaches to exploit the rich sentiment information inherent in the textual modality. However, these approaches often suffer from performance degradation d…
- Empirical Evaluation of Membership Inference Attacks on NLP Text Classifiers: A Baseline Study on SST-2William Novak, Muhammad Abusaqer · arXiv · Sep 10, 2026
Membership inference attacks (MIAs) try to determine whether a specific record was used to train a model, a privacy risk that matters in natural language processing (NLP), where training data can contain sensitive user text. This paper pres…
- An AFFA-Integrated Hybrid Deep Learning Framework for Explainable Sentiment AnalysisAyşe Aktuğ, Esra Calik Bayazit · Arabian Journal for Science... · Sep 7, 2026
- Stock Market Reaction of LQ45 U.S.-Trading PartnersHengky Surya Bhuana, Ida Bagus Anom Purbawangsa · Journal of Business Social ... · Sep 5, 2026
Background: The reciprocal tariff policy introduced by President Donald J. Trump on April 2, 2025, triggered widespread uncertainty across global financial markets, with notable implications for Indonesia’s equity market. International trad…
- A sentiment analysis of public opposition to carbon capture and storage technologyMabel San Román-Niaves, Sofia Morandini, Kalliopi Elli Fragouli, Helene Figari et al. · International journal of gr... · Sep 5, 2026
- HalluPeer: A Taxonomy-driven Benchmark for Detecting Hallucinations in Scientific Peer ReviewsTzu-Ling Lin, Dong-Ting Yao, Teng-Fang Hsiao, Wei-Chih Chen et al. · arXiv · Sep 3, 2026
The growing scale of academic peer review has motivated the use of Large Language Models (LLMs) as review assistants, yet LLMs can generate fluent but unsupported claims that undermine review reliability. Existing hallucination benchmarks a…
- C$^{3}$T: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation TreesS M Rafiuddin, Atriya Sen · arXiv · Sep 2, 2026
Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study why sentiment changes in rumor-centric conversation trees by…
- Research on Five-Category Classification of Comment Emotions Based on the Multi-agent RAG FrameworkBaohui Zhu · Applied and Computational E... · Sep 1, 2026
Because text comment sentiment analysis plays an essential role in applications such as online public opinion monitoring, user experience analysis, and intelligent customer service, it is rightly considered a core task of natural language p…
- Opinionated, Hesitant and Stressed: Three Studies of How Politicians Speak in Four Slavic ParliamentsIvan Porupski, Nikola Ljubešić · arXiv · Aug 31, 2026
We present three large-scale studies of spoken parliamentary speech across four Slavic languages (Croatian, Czech, Polish, Serbian), drawing on over 6,000 hours from the ParlaSpeech 3.0 corpus. The first study examines how utterance-level s…
- Generative Models Enhanced by Sequence Labelling and Aspect-Code Switching Improve Cross-lingual Aspect-Based Sentiment AnalysisJakub Šmíd, Pavel Přibáň, Pavel Král · arXiv · Aug 31, 2026
Cross-lingual aspect-based sentiment analysis (ABSA) transfers knowledge from a source language with annotated data to a target language, enabling fine-grained sentiment analysis without annotated target-language data. While monolingual ABS…
- Expectation, Backlash, Recovery, and Excitement: How Model Releases Shape Reddit Perceptions of Conversational AI SystemsVahid Rahimzadeh, Yury Zhauniarovich, Savvas Zannettou · arXiv · Aug 25, 2026
Conversational AI systems (CAISes) continuously change through model releases, feature updates, safety interventions, and access-policy shifts, yet user perceptions are often studied as static snapshots. We conduct a long-term, large-scale …
- SENSESHIFT: Continuous Sentiment-Controlled Text Generation via Encoder-based Mask InfillingShahed Masoudian, Markus Frohmann, Emmanouil Karystinaios, Navid Rekabsaz et al. · arXiv · Aug 25, 2026
Recent controllable text generation (CTG) for sentiment control has largely focused on decoder-based large language models, making causal attention the dominant paradigm. While effective for fluent generation, these models still struggle to…
- Robust Incomplete Multimodal Sentiment Analysis via Iterative Proxy CorrectionZhifa Geng, Subin Huang, Hao Guo, Junjie Chen et al. · arXiv · Aug 20, 2026
Multimodal sentiment analysis aims to infer affective states by integrating language, visual, and acoustic cues. However, real-world multimodal inputs are often incomplete or corrupted, which can weaken cross-modal complementarity and intro…
- Sentiment Analysis in Digital Spaces: An Overview of ReviewsLaura Eeva Maria Ayravainen, Joanne Hinds, Brittany I Davidson · ACM Computing Surveys · Aug 20, 2026
Digital data generated via social media have become a prosperous entity for sentiment analysis researchers seeking to understand individuals’ feelings, attitudes, and emotions. Numerous systematic reviews have synthesized work across divers…
- On the Fragility of Self-Improving Agents: Variance, Task Order, and UnderspecificationQinyuan Ye, Yu Li, Yada Pruksachatkun, Jiaxin Zhang et al. · arXiv · Aug 18, 2026
Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have shown great promise in recent literature. However, the reliability aspects of these methods…
- SpeechSense: A Paralinguistic-Focused Dataset for Fine-Grained Speech Sentiment AnalysisShicheng Ma, Wenqian Cui, Irwin King · arXiv · Aug 18, 2026
Recent advances in AI have revolutionized speech processing, yet effective speech understanding requires discerning not just what is said, but how it is said. Speech Sentiment Analysis plays a critical role in decoding these paralinguistic …
- From Entity Mentions to Tone: An LLM-Based Pipeline for Media Bias AnalysisKlesti Hoxha, Olti Qirici · arXiv · Aug 18, 2026
This paper presents a pipeline for analyzing media bias and framing in online news. The pipeline groups articles into topics and events, adds named-entity and sentiment annotations, and compares news sources through people mentions, source-…
- An Analysis of the Growth Patterns and Cultivation Pathways for Innovative Talents in Agriculture-Related Majors at Higher Vocational CollegesLiang Ke, Jian Yin · 现代高等教育研究 · Aug 18, 2026
The cultivation of agriculture-related talents in higher vocational colleges, transforming from skill based form to innovation-based one, is helpful to promote the revitalization of rural areas. This paper puts forward he growth law for suc…
- Institutional vs. Retail Information Channels for Cryptocurrency Market Intelligence: A Comparative Analysis of Signal Quality and Decision Support ImplicationsVarsha Ravindra Shetty, Mahesh Balan, Prajwal Vinod Naik, Nihaad Saleem et al. · Journal of the Association ... · Aug 15, 2026
The study examines how institutional news media (Google news) and retail social media (Reddit) function as distinct information channels for the cryptocurrency market. Analyzing 55,282 records with dual sentiment methods, hypothesis testing…
- ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media TextsChanh Vo, Son T. Luu, Ngan Luu-Thuy Nguyen · arXiv · Aug 13, 2026
This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user comments and 21,244 manually annotated opinion quadruples (source, target, expression, po…
- Large Language Model-Driven Small-Capitalization Trading: Integrating Financial News Sentiment, Macroeconomic Indicators, and Technical SignalsAlireza Kargarzadeh, Nariman Khaledian, Navid Parvini, Arman Khaledian · arXiv · Aug 12, 2026
Large language models can extract richer signals from financial news than fixed sentiment lexicons, and recent work has explored feeding such signals into portfolio construction. We study an uncertainty-aware construction that feeds model-p…
- Structuring the Space of PerspectivesAgnese Daffara, Sebastian Padó, Tanise Ceron · arXiv · Aug 12, 2026
The same event can be reported from different perspectives depending on the experiences, background, and beliefs of the writer or speaker. A variety of NLP areas engage with perspectives, spanning from text analysis to algorithm optimizatio…
- Multiclass Sentiment Analysis for Identifying Political ViewpointsGirma Yohannis Bade, Olga Kolesnikova, Jose Luis Oropeza, Grigori Sidorov · arXiv · Aug 11, 2026
The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and identify different political perspectives. Sentiment Analysis (SA) is a core task in Natu…
- An Exploratory Evaluation of LLM-Assisted Rewriting of Moderate-Complexity Financial Sentences for DisCoCat-Based Sentiment AnalysisBrian Llinas, Nikos Chrisochoides · arXiv · Aug 7, 2026
Quantum natural language processing (QNLP) provides a grammar-aware framework for text modeling, and Distributional Compositional Categorical (DisCoCat) is one of its theoretically grounded formulations. Prior work on financial sentiment an…
- VIBE: A VAD-Informed Benchmark for Entity-Centered Affective Profiling of Large Language Model OutputsAndrei Chetvergov, Alexander Evseev, Timofei Sivoraksha, Stepan Ukolov et al. · arXiv · Aug 4, 2026
Large language models routinely describe socially salient targets, including political figures, countries, religions, organizations, historical events, and social groups, encoding affective framing alongside factual content: a target may ap…
- Two-Stage Bengali Sentiment Classification: Domain Adaptation Through Continual Learning and Parameter-Efficient Fine-TuningMD Shaikh Rahman, Syed Maudud E Rabbi, Muhammad Mahbubur Rashid · arXiv · Aug 2, 2026
Understanding sentiment in low-resource languages remains a key challenge for Natural Language Processing (NLP), particularly when domain-specific data is scarce. In this work, we present SentiBanglaBERT, a two-stage Bengali sentiment class…