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AN EMPIRICAL EVALUATION OF CLASSICAL ALGORITHMS FOR SENTIMENT ANALYSIS FOR URDU TEXT
(UMT, Lahore, 2021) Abdul Mateen
Sentiment analysis has become one of the growing research areas related to the processing of natural languages and machine learning. There is a great deal of opinion and sentiment on particular topics available online, enabling many parties to discuss these views, such as clients, businesses and even governments. . The first task is to classify the text in terms of whether it expresses opinion or factual information Classification of polarities is the second activity that distinguishes between the polarities that sentences can bear (positive, negative or neutral). In terms of the English language, the study of natural language texts for the recognition of subjectivity and feeling has been well studied. The work carried out in terms of the Urdu language, on the other hand, remains in its infancy; hence, further collaboration between research communities is needed for them to give Urdu a mature sentiment analysis method. In this area, there are recognized challenges; some are inherited from the nature of the Urdu language itself, while others are derived from the scarcity of instruments and equipment from different sources. . In this research, we will construct a sentiment analyzer for Urdu text using a lexicon of Urdu sent units and their contextual information in a given sentence.