Identification and handling of intensifiers for enhancing accuracy of Urdu sentiment analysis

Abstract

AbstractJust like other languages, a large number of intensifiers are used in Urdu language. There may be a single occurrence of an intensifier or there may be multiple consecutive occurrences. While performing sentiment analysis of Urdu text, these intensifiers need special treatment for obtaining more accurate results, which is the main focus of this research work. A wide coverage Urdu sentiment lexicon is developed where intensifiers are identified and placed in a separate file. While developing Urdu sentiment analyser, rules are specifically formulated for assigning polarities to the intensifiers in text, if they are surrounded by the positive or negative words. Results show that the method proved to be effective in attaining the correct classification of Urdu sentences as positive, negative, or neutral, compared with traditional methods. Implementation of rules for intensifiers increased the accuracy of Urdu sentiment analyser from 78.33% to 83.42%, which is a statistically significant improvement. It is concluded that intensifiers cannot be ignored while performing sentiment analysis. Effective handling of intensifiers can significantly improve the performance of sentiment analyser.