Aspect-Based Sentiment Words and Their Polarities Using Chi-Square Test

Resumen

Most of the user-preferred products on e-commerce websites are accompanied by a massive number of product reviews and manually analyzing each review to understand the features and the user opinions associated with the products is an inconceivable task. A single domain of products can contain thousands of different products and an equally significant number of associated product features/aspects, thereby making the polarity of the sentiment words in the product reviews vary widely according to the aspect with which they are associated. The paper uses the Chi-square Test statistical measure to automatically calculate the aspect-based polarity of sentiment words in a given domain. The results of the method are tested on two different domains. The experimental results show that the method delivers an accuracy of more than 75% in both domains. The method also helps in discovering strong domain-specific polar adjectives that might be missing in universal sentiment lexicons.