LEXICON BASED RULE EXTRACTION FOR SENTIMENT ANALYSIS UNDER BIG DATA ENVIRONMENT

In today technology world, big data is generating from many sources like government, banks, social media, science, medical field and many others. This data is very much complex in terms of their properties and it requires some new tools and technologies to analyze. Sentiment analysis is the field of big data analysis which discovers the writer’s feeling and behaviour from his data. Behaviour of user can be analyzed as positive, negative or neutral. Lots of techniques can be used to do so. If beyond these polarities something can be done it will be very interesting. The main objective of this paper is to draw the next line in sentiment analysis under big data environment.  That line is to fetch information like what groups of users want to say. That will be extracted on the basis of their strength. Here strength means the frequency of that information or rule. This research paper proposed a new approach which is an extension to lexicon method has been introduced to find the rule extraction which can help in the area of sentiment analytics under the big data environment via Hadoop like approaches.