A Review of Urdu Sentiment Analysis with Multilingual Perspective: A Case of Urdu and Roman Urdu Language

Citation

Khan, Ihsan Ullah and Khan, Aurangzeb and Khan, Wahab and Mohd Su’ud, Mazliham and Alam, Muhammad Mansoor and Subhan, Fazli and Asghar, Muhammad Zubair (2022) A Review of Urdu Sentiment Analysis with Multilingual Perspective: A Case of Urdu and Roman Urdu Language. Computers, 11 (1). p. 3. ISSN 2073-431X

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Abstract

Research efforts in the field of sentiment analysis have exponentially increased in the last few years due to its applicability in areas such as online product purchasing, marketing, and reputation management. Social media and online shopping sites have become a rich source of user-generated data. Manufacturing, sales, and marketing organizations are progressively turning their eyes to this source to get worldwide feedback on their activities and products. Millions of sentences in Urdu and Roman Urdu are posted daily on social sites, such as Facebook, Instagram, Snapchat, and Twitter. Disregarding people’s opinions in Urdu and Roman Urdu and considering only resource-rich English language leads to the vital loss of this vast amount of data. Our research focused on collecting research papers related to Urdu and Roman Urdu language and analyzing them in terms of preprocessing, feature extraction, and classification techniques. This paper contains a comprehensive study of research conducted on Roman Urdu and Urdu text for a product review. This study is divided into categories, such as collection of relevant corpora, data preprocessing, feature extraction, classification platforms and approaches, limitations, and future work. The comparison was made based on evaluating different research factors, such as corpus, lexicon, and opinions. Each reviewed paper was evaluated according to some provided benchmarks and categorized accordingly. Based on results obtained and the comparisons made, we suggested some helpful steps in a future study.

Item Type: Article
Uncontrolled Keywords: Marketing, preprocessing, feature extraction, classification
Subjects: H Social Sciences > HF Commerce > HF5001-6182 Business > HF5410-5417.5 Marketing. Distribution of products
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 28 Jan 2022 03:24
Last Modified: 28 Jan 2022 03:24
URII: http://shdl.mmu.edu.my/id/eprint/9948

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