DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.
Title: Sentiment Analysis of Urdu Language Using Machine Learning Models
Authors: Haroon Yousaf, M. Imran Khan Khalil, Zia Ur Rahman, Firdous Ayub, Yousaf Khan, Asif Nawaz, Zeeshan Najam, Sheeraz Ahmed
Journal: Journal of Computing & Biomedical Informatics
Publisher: Research Center of Computing & Biomedical Informatics
Country: Pakistan
Year: 2025
Volume: 9
Issue: 1
Language: en
Keywords: Machine learningDeep learningUrdu LanguageNastaleeq Script
The purpose of the study was to develop sentiment analysis tool and system for Urdu language through the use of Machine Learning models and deep learning algorithms. In modern age of social media communication and interaction, the anlysis of opinion of the users and customer’s of business products, political discourses, religious and cultural crtiques and debates to explore their sentiments abouth the services, products, scenarios and stories are much needed. The methodology used by the researchers was to create dataset from tweets and posts on social media platforms in Urdu language. The researchers then used pre-processing and Lemmatization data to make it suitable for trainig and testing when using machine learning algorithms such as Support Vector Machine, Naïve Bayes, BiLSTM and other realted models.The sentiment analyzer categorized the sentiments in Urdu language text with nine categroies and thus the resulted tool or system was tested for its effectivness and efficeincy with more than 50% accuracy and high level of validaity were found. Thus, the sentiment analysis of Urdu language using machine learning models was deceloped to bbridge the gap in sentiment analysis for Urdu language in Pakistan.
Loading PDF...
Loading Statistics...