Intelligent Water Drop Based Sentiment Identification of Customer Reviews

Abstract

An organization real evaluation of performance done by its service or product user. User behavior is not unique or uniform, hence analysis directly depends on text reviews. As text leads to natural language processing so this paper has work in this field of customer review analysis for sentiment detection. Proposed model cluster the text patterns as per frequent connection obtained between the reviews. Intelligent water drop genetic algorithm was used for clustering the processed text patterns from the training dataset. Cluster text patterns were used to identify the sentiment class of the testing dataset. Experiment was done on real dataset obtained from twitter API. Results shown that proposed model has increase the work detection accuracy.