International Journal For Multidisciplinary Research

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Aspect-Based Sentiment Analysis

Author(s) A. Punitha, R. Keerthi Prabu, P. Devanathan, A. Sanjai, P. Bala
Country India
Abstract Aspect-Based Sentiment Analysis (ABSA) is an advanced NLP application that aims to identify aspect terms present in the given review and predict the sentiment associated with those aspect terms. ABSA is better than sentence-based sentiment classification because it considers the aspect terms present in the reviews to determine the sentiment rather than considering the individual sentence. Entrepreneurs could make use of ABSA to understand the customers' opinions about different aspects of their products or services. The task of Aspect-based sentiment analysis can be divided into two subtasks: Aspect Term Extraction (ATE) and Aspect Term Sentiment Classification (ATSC). In this paper, an SVM model is proposed for the task of ATE, and an Attention based LSTM model is proposed for the task of ATSC. The proposed models will be trained and tested on SemEval-2014 dataset.
Keywords Aspect-Based Sentiment Analysis, NLP, Aspect Term Extraction, Aspect Term Sentiment Classification, SVM and Attention based LSTM.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 5, Issue 3, May-June 2023
Published On 2023-05-27
Cite This Aspect-Based Sentiment Analysis - A. Punitha, R. Keerthi Prabu, P. Devanathan, A. Sanjai, P. Bala - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.3237
DOI https://doi.org/10.36948/ijfmr.2023.v05i03.3237
Short DOI https://doi.org/gr9r2k
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