Kian Kenyon-Dean, Eisha Ahmed, Scott Fujimoto, Jeremy Georges-Filteau, Christopher Glasz, Barleen Kaur, Auguste Lalande, Shruti Bhanderi, Robert Belfer, Nirmal Kanagasabai, Roman Sarrazingendron, Rohit Verma, Derek Ruths
| Challenge: | a dataset of over 7,000 tweets annotated with 5x coverage is used for sentiment analysis . a "complicated" class of sentiment is used to categorize text based on a predefined notion of sentiment . |
| Approach: | They propose to use a "complicated" class of sentiment to categorize tweets . they build a publicly available tweet sentiment analysis dataset . |
| Outcome: | The proposed classifiers perform better over a new publicly available TSA dataset . the classifier performance is compared with existing methods and improves on existing ones . |
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| Challenge: | a recent study shows that annotating sentiments is difficult and difficult. |
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Pranav Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman, Vipul Gupta, Rebecca Passonneau, Shomir Wilson
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Aspect-Based Sentiment Analysis as Fine-Grained Opinion Mining (2020.lrec-1)
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| Challenge: | a large body of research has been done on aspect-based sentiment analysis (ABSA) for almost two decades . aspect-Based sentiment analysis is a task that extracts sentiment/opinions from text in terms of targets . |
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| Challenge: | Recent work on document-level sentiment classification has shown that the sentiment in the original text is often hard to capture . previous studies focus on predicting the overall sentiment from original text using statistical or neural models, but these methods either heavily rely on human knowledge or suffer from the complex structure of the text. |
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| Challenge: | Recent dominance of machine learning-based natural language processing methods has overemphasized model accuracies rather than studying the reasons behind their errors. |
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Structured Sentiment Analysis as Dependency Graph Parsing (2021.acl-long)
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RD-MCSA: A Multi-Class Sentiment Analysis Approach Integrating In-Context Classification Rationales and Demonstrations (2025.emnlp-main)
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| Challenge: | Existing methods for multi-class sentiment analysis (MCSA) are difficult due to subtle semantic differences between adjacent sentiment levels and the scarcity of high-quality annotated data. |
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