In this first section, we will go through several general elements setting up the starting problem and the different challenges to overcome with text data. This is also the section in which we will discover our Twitter dataset, using libraries such as Pandas or Matplotlib.

Udemy Course Text Mining and Sentiment Analysis with Tableau and R NED Text Analysis 101: Sentiment Analysis in Tableau & R. At the Tableau Partner Summit in London I attended a session about statistics and sets in Tableau. In this session, Oliver Linder, Sales Consultant at Tableau Bestseller What you'll learn Connect Twitter and R to harvest Tweets for certain keywords Perform sentiment analysis based on a simple lexicon approach Clean and process Tweets for further analysis Export text based data and sentiment scores from R Use Tableau to visualize sentiment analysis data Identify situations where sentiment analysis can be applied in a company Description Extract valuable info out of Twitter for marketing, finance, academic or professional research and much more. This course harnesses the upside of R and Tableau to do sentiment analysis on Twitter data. With sentiment analysis you find out if the crowd has a rather positive or negative opinion towards a given search term. This search term can be a product (like in the course) but it can also be a person, region, company or basically anything as long as it is mentioned regularly on Twitter.

Over years, a crucial part of data-gathering behavior has revolved around what other people think. With the constantly growing popularity and availability of opinion-driven resources such as personal blogs and online review sites, new challenges and opportunities are emerging as people have started using advanced technologies to make decisions now. Sentiment analysis or opinion mining, refers to the use of computational linguistics, text analytics and natural language processing to identify and extract information from source materials. Sentiment analysis is considered one of the most popular applications of text analytics. The primary aspect of sentiment analysis includes data analysis on the body of the text for understanding the opinion expressed by it and other key factors comprising modality and mood.