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Learning Social Media Analytics with R

You're reading from   Learning Social Media Analytics with R Transform data from social media platforms into actionable business insights

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787127524
Length 394 pages
Edition 1st Edition
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Authors (4):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
Dipanjan Sarkar Dipanjan Sarkar
Author Profile Icon Dipanjan Sarkar
Dipanjan Sarkar
Karthik Ganapathy Karthik Ganapathy
Author Profile Icon Karthik Ganapathy
Karthik Ganapathy
Tushar Sharma Tushar Sharma
Author Profile Icon Tushar Sharma
Tushar Sharma
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with R and Social Media Analytics 2. Twitter – What's Happening with 140 Characters FREE CHAPTER 3. Analyzing Social Networks and Brand Engagements with Facebook 4. Foursquare – Are You Checked in Yet? 5. Analyzing Software Collaboration Trends I – Social Coding with GitHub 6. Analyzing Software Collaboration Trends II - Answering Your Questions with StackExchange 7. Believe What You See – Flickr Data Analysis 8. News – The Collective Social Media! Index

Summary


News data is a very important data source as it gives us a collective glimpse of the major themes in our day-to-day lives. We have witnessed how it can be a difficult process to collect news data and do some text mining on it. We have understood the basic concepts of web scraping, which is required in most data collections from the public domain. We have learned about the various problems we can have with textual data and how to work around them. An important point to mention about this chapter is the importance of maintaining an unbiased point of view while analyzing text data. Otherwise, it is very easy for text data mining to denigrate into a bad case of selection bias. Text data analysis is very diverse, a rapidly developing area of research, and tough to contain in one chapter. We encourage our readers to explore different text mining tools and find out what different use cases they can build on the datasets that we collected; this will certainly make for an interesting exercise...

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