The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis (2023.emnlp-main)
Copied to clipboard
Pranav Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman, Vipul Gupta, Rebecca Passonneau, Shomir Wilson
| Challenge: | Existing research reveals a notable absence of interdisciplinary endeavors to comprehend the social dimensions of sentiment analysis, encompassing aspects like emotion and fairness. |
| Approach: | They propose an ethics sheet encompassing critical inquiries to guide practitioners in ensuring equitable utilization of SA. |
| Outcome: | The proposed ethics sheet outlines the importance of adopting an interdisciplinary approach to defining sentiment in SA and offers a pragmatic solution for its implementation. |
Similar Papers
Sentiment Analysis: It’s Complicated! (N18-1)
Copied to clipboard
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 . |
A Comprehensive Survey of Contemporary Arabic Sentiment Analysis: Methods, Challenges, and Future Directions (2025.findings-naacl)
Copied to clipboard
| Challenge: | Existing literature on Arabic sentiment analysis is limited, compared to high-resourced languages such as English and French. |
| Approach: | They present a systematic review of existing literature on Arabic sentiment analysis focusing on research utilizing deep learning. |
| Outcome: | The proposed methods highlight gaps in the literature on Arabic sentiment analysis and outline promising directions for future research. |
Financial Sentiment Analysis: An Investigation into Common Mistakes and Silver Bullets (2020.coling-main)
Copied to clipboard
| Challenge: | Recent dominance of machine learning-based natural language processing methods has overemphasized model accuracies rather than studying the reasons behind their errors. |
| Approach: | They investigate the error patterns of some widely acknowledged sentiment analysis methods in the finance domain. |
| Outcome: | The proposed models are based on the existing models and have important clues for improving them. |
Language Technologies as If People Mattered: Centering Communities in Language Technology Development (2024.lrec-main)
Copied to clipboard
| Challenge: | Developing and deploying language technologies "as if people mattered" requires a reflexive and receptive approach, argues a new position paper . |
| Approach: | They argue that researchers should address linguistic and algorithmic injustice together with language communities to build strong interdisciplinary teams. |
| Outcome: | The authors argue that researchers should address social and linguistic injustice together with language communities to solve the challenges raised by language technologies. |
Financial Opinion Mining (2021.emnlp-tutorials)
Copied to clipboard
| Challenge: | This tutorial will provide an overview of financial opinion mining and provide research directions. |
| Approach: | This tutorial will introduce financial opinion mining and examine possible research directions. |
| Outcome: | This tutorial aims to provide an overview of financial opinion mining and figure out research directions. |
Structured Sentiment Analysis as Dependency Graph Parsing (2021.acl-long)
Copied to clipboard
| Challenge: | Structured sentiment analysis attempts to extract full opinion tuples from a text, but has been subdivided into smaller and smaller sub-tasks, e.g., target extraction or targeted polarity classification. |
| Approach: | They propose a framework which jointly predicts all elements of an opinion tuple and their relations by using dependency graph parsing. |
| Outcome: | The proposed framework improves on five datasets in English, Norwegian, Basque, and Catalan and refining the sentiment graphs with syntactic dependency information further improves results. |
A Survey of Computational Framing Analysis Approaches (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing computational methods for framing analysis are limited . a lack of a comprehensive understanding of framability is limiting the research . |
| Approach: | They propose to combine existing approaches to analyze large-scale datasets using computational methods. |
| Outcome: | The proposed methods will help scholars better understand how frames are being explored computationally, the authors argue . |
Automating Qualitative Data Analysis with Large Language Models (2024.acl-srw)
Copied to clipboard
| Challenge: | Existing methods for qualitative data analysis are far from resembling a human's analysis outcome. |
| Approach: | They propose a method based on Large Language Models to tackle automated coding and make it as close as possible to the results of human researchers. |
| Outcome: | The proposed method is based on large language models and can be as close as possible to the results of human researchers. |
Aspect-Based Sentiment Analysis as Fine-Grained Opinion Mining (2020.lrec-1)
Copied to clipboard
| 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 . |
| Approach: | They propose a meaning-preserving annotation scheme for aspect-based sentiment analysis . they then apply it to two popular ABSA datasets to examine their results . |
| Outcome: | The proposed approach improves the state of aspect-based sentiment analysis (ABSA) by preserving the meaning of the sentiment. |
HindiMD: A Multi-domain Corpora for Low-resource Sentiment Analysis (2022.lrec-1)
Copied to clipboard
| Challenge: | Social media platforms such as Twitter and Facebook are a new channel of information dissemination for many negative groups for recruitment. |
| Approach: | They propose to use a social media sentiment analysis corpus annotated with the sentiment classes positive, negative and neutral to investigate the polarity of user-expressed opinions. |
| Outcome: | The proposed model is based on a set of benchmark datasets for sentiment analysis across a range of domains and languages. |