Cloud Assisted Trend Analysis of Twitter Data using Hadoop
Aman Gupta, Ishaan Bhasin, Narinder Kaur · International journal of advance research, ideas and innovations in technology · 2018
In today‘s highly developed world, every minute, people around the globe express themselves via various platforms on the Web and in each minute, a huge amount of unstructured data is generated. This data is in the form of text which is gathered from forums and social media websites, such data is termed as big data. User opinions are related to a wide range of topics like politics, latest gadgets and products. These opinions can be mined using various technologies and are of utmost importance to make predictions or for one-to-one consumer marketing since they directly convey the viewpoint of the masses. Here we propose to analyze the sentiments of Twitter users through their tweets in order to extract what they think and find out the most trending events happening around the globe. Hence we are using hadoop and amazon web services for sentiment analysis which will process the huge amount of data on an amazon ec2 hadoop cluster faster.