{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sentiment-analysis-for-urdu-online-reviews","title":"Sentiment analysis for Urdu online reviews using deep learning models","arxiv_id":null,"date":"2021-06-28","proceeding":"Expert Systems 2021 6","authors":["qra Safder","Zainab Mahmood","Raheem Sarwar","Saeed-Ul Hassan","Farooq Zaman","Rao Muhammad Adeel Nawab","Faisal Bukhari","Rabeeh Ayaz Abbasi","Salem Alelyani","Naif Radi Aljohani","Raheel Nawaz"],"abstract":"Most existing studies are focused on popular languages like English, Spanish, Chinese,\r\nJapanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning\r\nmodel for the sentiments expressed in this under-resourced language. We develop\r\nan open-source corpus of 10,008 reviews from 566 online threads on the topics of\r\nsports, food, software, politics, and entertainment. The objectives of this work are bifold (a) the creation of a human-annotated corpus for the research of sentiment analysis in Urdu; and (b) measurement of up-to-date model performance using a corpus.\r\nFor their assessment, we performed binary and ternary classification studies utilizing\r\nanother model, namely long short-term memory (LSTM), recurrent convolutional neural network (RCNN) Rule-Based, N-gram, support vector machine , convolutional neural network, and LSTM. The RCNN model surpasses standard models with 84.98%\r\naccuracy for binary classification and 68.56% accuracy for ternary classification. To\r\nfacilitate other researchers working in the same domain, we have open-sourced the\r\ncorpus and code developed for this research","url_abs":"https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12751","url_pdf":"https://www.researchgate.net/profile/Farooq-Zaman/publication/353333756_Sentiment_analysis_for_Urdu_online_reviews_using_deep_learning_models/links/6113c7891e95fe241ac43e53/Sentiment-analysis-for-Urdu-online-reviews-using-deep-learning-models.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sentiment-analysis-for-urdu-online-reviews","repo_url":"https://github.com/farooqzaman1/Urdu_sentiment_analysis","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"binary-classification","task_name":"Binary Classification"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"r-cnn","method_name":"R-CNN"},{"method_slug":"svm","method_name":"SVM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[{"slug":"urdu-online-reviews","name":"Urdu Online Reviews","full_name":"Urdu Online Reviews"}],"methods_introduced":[],"results":[{"leaderboard":"/sota/sentiment-analysis-on-urdu-online-reviews","task":"Sentiment Analysis","dataset":"Urdu Online Reviews","model":"RCNN","rank_in_archive_order":1,"of":1,"metrics":{"Average F1":"84.48"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}