An Intelligent Unsupervised Approach for Handling Context-Dependent Words in Urdu Sentiment Analysis-Reference-Cited by-同舟云学术

An Intelligent Unsupervised Approach for Handling Context-Dependent Words in Urdu Sentiment Analysis

Published:2022-04-29 Issue:5 Volume:21 Page:1-15
ISSN:2375-4699
Container-title:ACM Transactions on Asian and Low-Resource Language Information Processing
language:en
Short-container-title:ACM Trans. Asian Low-Resour. Lang. Inf. Process.

Author:

Mukhtar Neelam¹^ORCID,Abid Khan Mohammad¹,Chiragh Nadia¹,Nazir Shah²,Ullah Jan Asim³

Affiliation:

1. University of Peshawar, Peshawar, KPK, Pakistan

2. University of Swabi, Swabi, KPK, Pakistan

3. Abasyn University, Peshawar, KPK, Pakistan

Abstract

The characteristic of context dependency in Urdu words needs to be handled carefully while performing Urdu sentiment analysis. In this research, an already constructed Urdu sentiment lexicon of positive and negative words is further expanded by the addition of context-dependent words. These context-dependent words are used with or without conjunctions. Rules are formulated for assigning polarities to those context-dependent words that are surrounded by the positive or negative words. These rules were incorporated in the Urdu sentiment analyzer. Fusion of these rules for handling context-dependent words and the expanded Urdu sentiment lexicon resulted in increasing the accuracy of the Urdu sentiment analyzer from 83.43% to 89.03% with 0.8655 precision, 0.9053 recall, and 0.8799 F-measure, which is a statistically significant improvement.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Link

https://dl.acm.org/doi/pdf/10.1145/3510830

Reference43 articles.

1. Affective Computing and Sentiment Analysis

2. Survey on Aspect-Level Sentiment Analysis

3. Sentiment Analysis and Opinion Mining

4. Aspect extraction for opinion mining with a deep convolutional neural network

5. Visual and Textual Sentiment Analysis of a Microblog Using Deep Convolutional Neural Networks

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