A REVIEW PAPER ON PARALLELED BIG DATA ALGORITHM WITH MAPREDUCE FRAMEWORK FOR MINING TWITTER DATA

Communication is a key factor in today’s human life, due to time constraints physical interaction between people is not possible. This gap is filled by the technology through ‘social networking’ sites it’s very easy to get access to interact other based on their interests. Many applications are getting releasing with new features day-by-day from vendors, to provide efficient usability and user friendliness. This paper proposes a new system that delivers large database of Social Networking Site (SNS) called ‘Twitter’. Many Third party application are building based on SNS like Twitter, they need to have processed data from their operational purpose. The main stream of the applications is visualization applications. This paper gives more beneficial solution by providing in-depth detailed information of data. In this context this implementation serves processed information of tweets accessed from Twitter Server. Here processing the tweet involves extraction of metadata of tweet, geocoding the physical address in a tweet, analyzing the sentiment of content in the tweet text and extracting the significant and key phrases from a text. This application is an integrated system used to get connect and access tweets from Twitter to get processed text analysis components. After all the Information Extracted and NER (Named Entity Recognition) text analysis from tweet, are stored into a persistence database.