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Mastering Social Media Mining with R

You're reading from   Mastering Social Media Mining with R Extract valuable data from your social media sites and make better business decisions using R

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784396312
Length 248 pages
Edition 1st Edition
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Table of Contents (8) Chapters Close

Preface 1. Fundamentals of Mining 2. Mining Opinions, Exploring Trends, and More with Twitter FREE CHAPTER 3. Find Friends on Facebook 4. Finding Popular Photos on Instagram 5. Let's Build Software with GitHub 6. More Social Media Websites Index

Summary

In this chapter, you gained knowledge of the various Twitter APIs. We discussed how to create a connection with Twitter, and we saw how to retrieve tweets with various attributes. We saw the power of Twitter in helping us determine customers' attitudes toward today's various businesses. The activity can be done on a weekly basis, and one easily get the monthly, quarterly, or yearly changes in customer sentiment. This can not only help the customer decide the trending business, but also the business itself can get a well-defined metric of its own performance. It can use such scores/graphs to improve. We also discussed various methods of sentiment analysis, varying from basic word-matching the advanced Bayesian algorithms. In the next chapter, we will apply a similar analysis to Facebook.

You have been reading a chapter from
Mastering Social Media Mining with R
Published in: Sep 2015
Publisher:
ISBN-13: 9781784396312
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