research-article

Pashto Sentiment Analysis Using Lexical Features

Authors:

Arif Ur RahmanAuthors Info & Claims

MedPRAI-2016: Proceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence

Pages 121 - 124

https://doi.org/10.1145/3038884.3038904

Published: 22 November 2016 Publication History

Abstract

Individuals use various platforms to express their opinion regarding products, services, political situations and other events. Knowing the opinion of people is very important for the concerned individuals and organizations in order to devise future strategies according to the wishes of people. The present research study focuses on extraction of opinion from digital-born Pashto text. The study involved the creation of multiple state-of-the-art classifiers by adapting methodology of message level task using sentiment analysis of Tweets'. In addition to this, word-sentiment lexicons with tokenization of sentences and translation of existing English lexicons were generated. The findings show that lexical features based Pashto sentiment analysis extracts sentiments with a high accuracy.

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Cited By

Khan MNaseer AWali ATamoor M(2024)A Roman Urdu Corpus for sentiment analysisThe Computer Journal10.1093/comjnl/bxae05267:9(2864-2876)Online publication date: 18-Jun-2024
https://doi.org/10.1093/comjnl/bxae052
Altaf AAnwar MJamal MBajwa URani S(2024)Aspect-based sentiment analysis in Urdu language: resource creation and evaluationNeural Computing and Applications10.1007/s00521-024-10145-xOnline publication date: 28-Aug-2024
https://doi.org/10.1007/s00521-024-10145-x
Khan SNazir SKhan H(2023)Analysis of Cursive Text Recognition Systems: A Systematic Literature ReviewACM Transactions on Asian and Low-Resource Language Information Processing10.1145/359260022:7(1-30)Online publication date: 13-Apr-2023
https://dl.acm.org/doi/10.1145/3592600
Show More Cited By

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cover image ACM Other conferences

MedPRAI-2016: Proceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence

November 2016

163 pages

ISBN:9781450348768

DOI:10.1145/3038884

General Chairs:
Chawki Djeddi
Larbi Tebessi University, Algeria
,
Imran Siddiqi
Bahria University, Pakistan
,
Akram Bennour
Larbi Tebessi University, Algeria
,
Program Chairs:
Youcef Chibani
University of Science and Technology Houari Boumediene, Algeria
,
Haikal El Abed
Technical Trainers College, German International Cooperation, Kingdom of Saudi Arabia

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2016

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MedPRAI-2016

MedPRAI-2016: Mediterranean Conference on Pattern Recognition and Artificial Intelligence

November 22 - 23, 2016

Tebessa, Algeria

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Cited By

Khan MNaseer AWali ATamoor M(2024)A Roman Urdu Corpus for sentiment analysisThe Computer Journal10.1093/comjnl/bxae05267:9(2864-2876)Online publication date: 18-Jun-2024
https://doi.org/10.1093/comjnl/bxae052
Altaf AAnwar MJamal MBajwa URani S(2024)Aspect-based sentiment analysis in Urdu language: resource creation and evaluationNeural Computing and Applications10.1007/s00521-024-10145-xOnline publication date: 28-Aug-2024
https://doi.org/10.1007/s00521-024-10145-x
Khan SNazir SKhan H(2023)Analysis of Cursive Text Recognition Systems: A Systematic Literature ReviewACM Transactions on Asian and Low-Resource Language Information Processing10.1145/359260022:7(1-30)Online publication date: 13-Apr-2023
https://dl.acm.org/doi/10.1145/3592600
Noor FBakhtyar MBaber J(2019)Sentiment Analysis in E-commerce Using SVM on Roman Urdu TextEmerging Technologies in Computing10.1007/978-3-030-23943-5_16(213-222)Online publication date: 14-Jul-2019
https://doi.org/10.1007/978-3-030-23943-5_16

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