Papers with Aspect Based Sentiment Analysis
Resource Creation and Evaluation of Aspect Based Sentiment Analysis in Urdu (2020.aacl-srw)
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| Challenge: | Recent work on ABSA in Urdu language has limitations. |
| Approach: | They propose to create a dataset for Aspect Based Sentiment Analysis in Urdu language which will support multiple aspects. |
| Outcome: | The proposed dataset will provide a baseline evaluation for ABSA systems in Urdu language. |
InterpreT: An Interactive Visualization Tool for Interpreting Transformers (2021.eacl-demos)
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Vasudev Lal, Arden Ma, Estelle Aflalo, Phillip Howard, Ana Simoes, Daniel Korat, Oren Pereg, Gadi Singer, Moshe Wasserblat
| Challenge: | Using Transformer-based models for NLU/NLP tasks is a growing interest . but there are many open questions regarding the behavior of these models . |
| Approach: | They present an interactive visualization tool for interpreting Transformer-based models. |
| Outcome: | The tool can track and visualize token embeddings through each layer of a Transformer, highlight distances between certain token embeds, and identify task-related functions of attention heads using new metrics. |
A Hybrid Approach to Aspect Based Sentiment Analysis Using Transfer Learning (2024.lrec-main)
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| Challenge: | Aspect-Based Sentiment Analysis (ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. |
| Approach: | They propose a hybrid approach to Aspect-Based Sentiment Analysis using transfer learning . they exploit the strengths of large language models and traditional syntactic dependencies . |
| Outcome: | The proposed method exploits the strengths of large language models and traditional syntactic dependencies. |
Target-specified Sequence Labeling with Multi-head Self-attention for Target-oriented Opinion Words Extraction (2021.naacl-main)
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| Challenge: | Recent studies on ABSA focus on Target-oriented Opinion Words (or Terms) Extraction . Experimental results indicate that TSMSA outperforms the benchmark methods on TOWE significantly . |
| Approach: | They propose to use a pre-trained language model with multi-head self-attention to integrate TOWE with AOPE to extract aspects and opinion terms in pairs. |
| Outcome: | The proposed structure outperforms the benchmark methods on TOWE significantly . the proposed structure is similar or even better than state-of-the-art AOPE models . |
Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling (N19-1)
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| Challenge: | Opinion target extraction and opinion words extraction are two fundamental subtasks in Aspect Based Sentiment Analysis (ABSA). |
| Approach: | They propose a new subtask for Aspect Based Sentiment Analysis to extract opinion words as pairs from a given opinion target. |
| Outcome: | The proposed model outperforms existing methods significantly on several popular ABSA benchmarks. |
AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis (2022.emnlp-main)
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| Challenge: | Aspect Based Sentiment Analysis is a dominant research area with potential applications in social media analytics, business, finance, and health. |
| Approach: | They propose a weakly supervised multi-label Aspect Category Sentiment Analysis framework which does not use any labelled data. |
| Outcome: | The proposed framework outperforms weakly supervised baselines on four benchmark datasets and is able to generate multiple aspect category-sentiment pairs per review sentence. |
Complex and Precise Movie and Book Annotations in French Language for Aspect Based Sentiment Analysis (L18-1)
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| Challenge: | Aspect Based Sentiment Analysis (ABSA) aims at collecting detailed opinion information according to products and their features. |
| Approach: | They propose to use linguistics tools to enhance text classification with aspect-based sentiment analysis. |
| Outcome: | The proposed method is based on two French online reviews datasets. |
Dataset Creation and Evaluation of Aspect Based Sentiment Analysis in Telugu, a Low Resource Language (2020.lrec-1)
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| Challenge: | Aspect Based Sentiment Analysis (ABSA) is a finer level sentiment analysis that assigns polarity to each targeted aspect instead of the entire review. |
| Approach: | They propose to use Telugu as a language for aspect based sentiment analysis . they use a resource that can be used to classify and categorise aspects of a review . |
| Outcome: | The proposed resource is based on a set of tasks in Telugu which demonstrate its reliability and usefulness. |