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Showing posts from July, 2017

Sentiment Analysis Using R

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Twitter Sentiment Analysis and GST Twitter Authorization and Fetch Twitter Timeline Data Twitter, over the years has become the single place to voice our thoughts. Even though it has a character limitation of 140 characters, the sheer volume of tweets generated is massive. In this post we analyze the reactions to the newly implemented Goods and Services Tax. The code is followed by a step-by-step instruction-cum-explanation part. Do go through it for proper execution. Some quick facts about twitter! Created in March 2006 by Jack Dorsey, Evan Williams, Biz Stone and Noah Glass, Twitter was launched in July 2006 and the first tweet was sent by Jack Dorsey on 21 March 2006. Within 10 years of its operation Twitter has over a billion accounts and 300 million active users. There are over 500 million users who visit the social media website each month without logging in.  500 million tweets are sent every day i.e. every second adds 6000 tweets. This is enou

Introduction to R

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Installing R, Packages in R, Data Types in R Let's start the course! But before we do, let us address a few questions. 1.  What is data science ? 2. Why data science? 3. Why R for data science? Data Science Well the name itself gives you an idea but then again, everything must have a complex definition like this:  " Data science is a multidisciplinary blend of  data inference, algorithm development, and technology  in order to solve analytically complex problems ." In simpler words, a field which aims to provide a meaning to vast amounts of complex data. Everyday tons and tons of data is generated from sensors, websites, social media, e-commerce and other sectors. Even though with a larger volume of data you might get better averages, but then there is a lot of noise i.e. useless data as well. To extract useful information to enable decision making is a data scientist's job.