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Mastering Spark for Data Science

You're reading from   Mastering Spark for Data Science Lightning fast and scalable data science solutions

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785882142
Length 560 pages
Edition 1st Edition
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Authors (5):
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 Bifet Bifet
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Bifet
 Morgan Morgan
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Morgan
 Amend Amend
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Amend
 Hallett Hallett
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Hallett
 George George
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George
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Table of Contents (22) Chapters Close

Mastering Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. The Big Data Science Ecosystem FREE CHAPTER 2. Data Acquisition 3. Input Formats and Schema 4. Exploratory Data Analysis 5. Spark for Geographic Analysis 6. Scraping Link-Based External Data 7. Building Communities 8. Building a Recommendation System 9. News Dictionary and Real-Time Tagging System 10. Story De-duplication and Mutation 11. Anomaly Detection on Sentiment Analysis 12. TrendCalculus 13. Secure Data 14. Scalable Algorithms

Chapter 11. Anomaly Detection on Sentiment Analysis

When we look back at the year 2016, we will surely remember it as a time of many significant geo-political events ranging from Brexit, Great Britain's vote to leave the European Union, to the untimely passing of many beloved celebrities, including the sudden death of the singer David Bowie (covered in Chapter 6, Scraping Link-Based External Data and Chapter 7, Building Communities). However, perhaps the most notable occurrence of the year was the tense US presidential election and its eventual outcome, the election of President Donald Trump. A campaign that will long be remembered, not least for its unprecedented use of social media, and the stirring up of passion among its users, most of whom made their feelings known through the use of hashtags: either positive ones, such as #MakeAmericaGreatAgain or #StrongerTogether, or conversely negative ones, such as #DumpTrump or #LockHerUp. Since this chapter is about sentiment analysis, the election...

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