Social Media Data Mining and Analytics
by Gabor Szabo and Oscar Boykin


Overview - Harness the power of social media to predict customer behaviorand improve sales

Social media is the biggest source of Big Data. Because of this,90% of Fortune 500 companies are investing in Big Data initiativesthat will help them predict consumer behavior to produce bettersales results.  Read more...


 
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More About Social Media Data Mining and Analytics by Gabor Szabo; Oscar Boykin
 
 
 
Overview
Harness the power of social media to predict customer behaviorand improve sales

Social media is the biggest source of Big Data. Because of this,90% of Fortune 500 companies are investing in Big Data initiativesthat will help them predict consumer behavior to produce bettersales results. Written by Dr. Gabor Szabo, a Senior Data Scientistat Twitter, and Dr. Oscar Boykin, a Software Engineer at Twitter, Social Media Data Mining and Analytics shows analysts how touse sophisticated techniques to mine social media data, obtainingthe information they need to generate amazing results for theirbusinesses.

Social Media Data Mining and Analytics isn't just anotherbook on the business case for social media. Rather, this bookprovides hands-on examples for applying state-of-the-art tools andtechnologies to mine social media - examples include Twitter, Facebook, Pinterest, Wikipedia, Reddit, Flickr, Web hyperlinks, andother rich data sources. In it, you will learn:

  • The four key characteristics of online services-users, socialnetworks, actions, and content
  • The full data discovery lifecycle-data extraction, storage, analysis, and visualization
  • How to work with code and extract data to create solutions
  • How to use Big Data to make accurate customer predictions

Szabo and Boykin wrote this book to provide businesses with thecompetitive advantage they need to harness the rich data that isavailable from social media platforms.


 
Details
  • ISBN-13: 9781118824856
  • ISBN-10: 1118824857
  • Publisher: Wiley
  • Publish Date: October 2018
  • Page Count: 432


Related Categories

Books > Computers > Databases - Data Warehousing
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