Sentiment Analysis of Roman Text: Challenges, Opportunities, and Future Directions

Abstract

The rise of social media platforms has sparked significant interest among Natural Language Processing (NLP) researchers in Sentiment Analysis over the past few decades. Numerous studies have focused on analyzing the sentiment of different languages, including Urdu, which is widely spoken in South Asia and serves as the national language of Pakistan. While considerable research has been conducted on sentiment analysis using Machine Learning (ML), Deep Learning (DL), and other methods, Roman Urdu sentiment analysis holds equal importance. This paper presents a comprehensive analysis of existing literature on sentiment analysis of various languages, with a specific focus on Roman text and approaches such as ML, DL, and others. Additionally, the paper proposes new directions for future researchers in this field.