Authors : Mostafa A. Nofal, Sahar F. Sabbeh and Khaled M. Fouad
Abstract: Customers like online submitting unstructured reviews that has turned out a popular way to come across sentiments across the products purchased or services extradited. In each review, customer typically submit about both the positive and negative opinion of the product, although, the general sentiment toward that product may be positive or negative. The sentiment analysis tries to extract sentiments and subjectivity of customer reviews. These reviews can be beneficial for gathering sentiments of customers about products by analyzing it. However, this analysis should derive careful consideration of customer’s anonymity and the privacy of the sensitive data because a privacy is a significant concern for either customers and enterprises. In this research, automatic analysis of sentiment is carried out to achieve such detailed aspects based on domain ontology. Sentiment analysis recognizes the features in the sentiment and classify the sentiments of the review for each of these features. In the proposed approach, the sentiment polarity and polarity strength are provided and computed using fuzzy set. The fuzzy set theory is just effective in processing natural languages because it measures the vagueness. The fuzzy set theory is effective in analyzing reviews which are generally in natural languages. Additionally, the proposed system takes privacy into consideration by masking data before final publishing. The evaluation of the proposed approach is based on using dataset of London restaurant’s reviews on TripAdvisor. The evaluation utilizes three different classifiers MLP, SVM and NB and utilizes 5×2-fold cross validation for four evaluation measures; accuracy, precision, recall and F1.
Mostafa A. Nofal, Sahar F. Sabbeh and Khaled M. Fouad, 2020. Privacy Preserving Mining of Web Reviews Based on Sentiment Analysis and Fuzzy Sets. Asian Journal of Information Technology, 19: 122-136.