Social Media Mining with R

Social Media Mining with R
Author: Richard Heimann
Publisher: Packt Pub Limited
Total Pages: 122
Release: 2014
Genre: Computers
ISBN: 9781783281770

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A concise, handson guide with many practical examples and a detailed treatise on inference and social science research that will help you in mining data in the real world.Whether you are an undergraduate who wishes to get handson experience working with social data from the Web, a practitioner wishing to expand your competencies and learn unsupervised sentiment analysis, or you are simply interested in social data analysis, this book will prove to be an essential asset. No previous experience with R or statistics is required, though having knowledge of both will enrich your experience.


Social Media Mining with R
Language: en
Pages: 122
Authors: Richard Heimann
Categories: Computers
Type: BOOK - Published: 2014 - Publisher: Packt Pub Limited

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A concise, handson guide with many practical examples and a detailed treatise on inference and social science research that will help you in mining data in the
Social Media Mining with R
Language: en
Pages:
Authors: Nathan Danneman
Categories:
Type: BOOK - Published: 2014 - Publisher:

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Social Media Mining
Language: en
Pages: 337
Authors: Reza Zafarani
Categories: Computers
Type: BOOK - Published: 2014-04-28 - Publisher: Cambridge University Press

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Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.
Mastering Social Media Mining with R
Language: en
Pages: 248
Authors: Sharan Kumar Ravindran
Categories: Computers
Type: BOOK - Published: 2015-09-23 - Publisher: Packt Publishing Ltd

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Extract valuable data from your social media sites and make better business decisions using R About This Book Explore the social media APIs in R to capture data
Text Mining with R
Language: en
Pages: 193
Authors: Julia Silge
Categories: Computers
Type: BOOK - Published: 2017-06-12 - Publisher: "O'Reilly Media, Inc."

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Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Fa