Papers with polarity classification
If you’ve got it, flaunt it: Making the most of fine-grained sentiment annotations (2021.eacl-main)
Copied to clipboard
| Challenge: | a recent study shows that annotating sentiments is difficult and difficult. |
| Approach: | They propose to integrate holder and expression information into sentiment analysis to improve target extraction . they perform experiments on eight English datasets to determine whether annotating expressions improves target extraction. |
| Outcome: | The proposed approach improves target extraction and classification on English datasets. |
Identifying Emotional and Polar Concepts via Synset Translation (2024.starsem-1)
Copied to clipboard
| Challenge: | Emotion identification and polarity classification seek to determine sentiment expressed by a writer. |
| Approach: | They propose a translation-based method for labeling each individual word sense and lexical concept into 20 different languages and translate them into multilingual sentiment lexicons. |
| Outcome: | The proposed method outperforms existing methods and is available on GitHub . it contains 12,429 emotional synsets and 15,567 polar synset. |
Enhancing General Sentiment Lexicons for Domain-Specific Use (C18-1)
Copied to clipboard
| Challenge: | Lexicon based methods for sentiment analysis rely on high quality polarity lexicons. |
| Approach: | They evaluate SentProp framework for inducing domain-specific polarities from word embeddings and use it to enhance a general-purpose lexicon for use in the political domain. |
| Outcome: | The proposed framework performs worse than the original lexicon in an out-domain task, showing that the words added and the polarity shifts applied are domain-specific and do not translate well to an out domain setting. |
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. |
Building a Sentiment Corpus of Tweets in Brazilian Portuguese (L18-1)
Copied to clipboard
| Challenge: | Sentiment analysis is a popular area of Natural Language Processing due to its subjective and semantic characteristics. |
| Approach: | They propose to annotate Brazilian Portuguese sentences manually using a sentiment corpus . they run experiments on polarity classification using six machine learning classifiers . |
| Outcome: | The proposed method is based on a Brazilian Portuguese sentiment corpus and achieved 80.38% on F-Measure and 64.87% when including the neutral class. |
KazSAnDRA: Kazakh Sentiment Analysis Dataset of Reviews and Attitudes (2024.lrec-main)
Copied to clipboard
| Challenge: | Currently, sentiment analysis is a widely employed text classification task that involves extracting the sentiment expressed by individuals towards a variety of entities. |
| Approach: | They propose to use KazSAnDRA to automate Kazakh sentiment analysis by developing and evaluating four machine learning models for polarity and score classification. |
| Outcome: | The proposed dataset is the first and largest publicly available dataset of its kind. |