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RStudio for R Statistical Computing Cookbook

You're reading from   RStudio for R Statistical Computing Cookbook Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781784391034
Length 246 pages
Edition 1st Edition
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Author (1):
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Andrea Cirillo Andrea Cirillo
Author Profile Icon Andrea Cirillo
Andrea Cirillo
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Table of Contents (10) Chapters Close

Preface 1. Acquiring Data for Your Project 2. Preparing for Analysis – Data Cleansing and Manipulation FREE CHAPTER 3. Basic Visualization Techniques 4. Advanced and Interactive Visualization 5. Power Programming with R 6. Domain-specific Applications 7. Developing Static Reports 8. Dynamic Reporting and Web Application Development Index

Performing a Twitter sentiment analysis


Twitter sentiment analysis is another powerful tool in the text analytics toolbox.

With sentiment analysis, we can analyze the mood expressed within a text.

In this recipe, we will download tweets relating to "data science with R" and perform a sentiment analysis on them, employing the bag of word technique.

The main feature of this technique is not trying to understand the meaning of the analyzed text but just looking at one word at the time, seeing whether it expresses a positive or negative sentiment.

Our example will therefore result in computing the overall sentiment around the topic, algebraically summing up the sentiment score of every single word in our bag.

Getting ready

This recipe will leverage powerful functions from three different packages: one for downloading tweets, one for string manipulation, and the last one for text analytics activities.

We therefore need to install and load those packages:

install.packages(c("twitteR","stringr","tm")...
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