Integration of Sentiment Analysis engine with Big Data with Lexical Based approach

In today’s environment there are various applications which are producing large amount of data. These data items requires analysis for use this data for certain useful purpose in the industries. These processed data items can useful for understanding the behavior of the person present on the social media places. In current research paper data belongs to various social media sites is being processed using Hadoop and processed data will be stored into the MongoDB. Later on using certain simulator data will be processed to generate the comparative analysis. The proposed approach based on the Lexical based analysis is applied for the data analysis and classification purpose. The data extracted after lexical analysis will be compared to the ontology of the generated positive and negative words. The proportional positive and negative classification is done for the analyzed data. This will help in identifying the sentiments of the people about certain items for which the data is being shared. The proposed approach is compared to the existing approach based on different parameters like Accuracy, Time and the Error Rate. The proposed approach is giving better results. That means provides better accuracy, less time for the computation and less error rate.