Aspect Based Sentiment Analysis in Text Reviews.

Date of Submission

December 2020

Date of Award

Winter 12-12-2021

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)


Garain, Utpal (CVPR-Kolkata; ISI)

Abstract (Summary of the Work)

Sentiment analysis plays an important role in e-commerce, as it allows the industries to better understand the customer experience and its brand value. Aspect Based Sentiment Analysis (ABSA) is a fine-grained version of sentiment analysis. ABSA not only focuses on analysing opinions in a given review but also looks into the several aspects and their sentiments thus giving a much clearer understanding. Aspect extraction is a crucial part of this ABSA task on which much attention has not been paid until recent years. Limited number of training data has made the task further challenging. This project addresses the problem of extraction of aspects from review comments and thereby attempts to improve the state of the art results in ABSA. For language modeling, BERT is used and it's fine-tuned on a novel Neurosyntactic model architecture. POS and dependency tags are used along review comments for extraction of aspect terms. Experiments conducted on SemEval dataset show that the proposed architecture achieves the state of the art results on the dataset.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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