Sentiment Analysis On User Reviews Through Lexicon And Rule-Based Approach

Computers need data and humans need information. The process of converting data into useful information needs analysis to be done onto it. Reviews of customers are valuable as they are an important source of data for multiple purposes. However, these feedbacks are subjective, so extraction of information is not an easy task. This paper presents a different method of sentiment analysis research on reviews. The main focus is the data mining from multiple trustworthy sites and categorization of this data. The results are efficient and better than available multiple approaches. The paper concludes with recommendations and future work for giving a new direction to ontology-based opinion mining.