Abstract
The proposed work aims to collect correct reviews on movies using sentiment analysis. It classifies movie review into polarity classes based on the sentences and considers the biasness of user with respect to star cast of the film. Additionally, personality vector is also added to improve results. These two factors are used to minimize the biasness in the feature set to create hypothesis. The results with and without attribute of biasness are evaluated with different classification algorithms on twitter dataset. Results of the proposed work suggest that when removing biasing from movie review can give honest reviews.
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Rathore, A.S., Arjaria, S., Khandelwal, S., Thorat, S., Kulkarni, V. (2019). Movie Rating System Using Sentiment Analysis. In: Ray, K., Sharma, T., Rawat, S., Saini, R., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 742. Springer, Singapore. https://doi.org/10.1007/978-981-13-0589-4_9
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DOI: https://doi.org/10.1007/978-981-13-0589-4_9
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