Sentiment Analysis using Twitter Data

Analysis of any particular product or entity can be done using the wide collection of unstructured data obtained from the Internet (World Wide Web). Many industrial and survey companies are using this data analysis to take decisions. In this paper, we want to show how effectively, sentiment analysis can be done on the data collected from the social networking website called Twitter, using Flume. Twitter is an online web application containing rich amounts of data that can be an un-structured, semi-structured or structured data. The Twitter data can be collected by using BIGDATA eco-system, using online streaming tool called Flume. In this project, the type of analysis we’re concentrating on is Sentiment analysis. Using Hive and its queries to give the sentiment data based on the groups that are defined in the HQL (Hive Query Language). Here we have categorized this sentiment analysis into 3 groups of tweets that have positive, moderate and negative comments.