Social media data mining and analytics

Resource Information

The work Social media data mining and analytics represents a distinct intellectual or artistic creation found in University of Missouri Libraries. This resource is a combination of several types including: Work, Language Material, Books.

Label

Social media data mining and analytics

Statement of responsibility

Gabor Szabo, Gungor Polatkan, Oscar Boykin, Antonios Chalkiopoulos

Title variation

Data mining and analytics

Creator

• Szabó, Gábor

Contributor

• Polatkan, Gungor
• Chalkiopoulos, Antonios
• Boykin, Oscar

Author

• Szabó, Gábor
• Boykin, Oscar
• Chalkiopoulos, Antonios
• Polatkan, Gungor

Subject

• Consumer behavior -- Forecasting
• Consumer profiling -- Data processing
• Data mining
• Data mining
• Business planning -- Data processing
• Social media -- Data processing
• Data mining
• Business planning -- Data processing
• Business planning -- Data processing
• Consumer behavior -- Forecasting
• Consumer behavior -- Forecasting

Language

eng

Summary

"Social media is a rich source of big data, so much so that 90% of Fortune 500 companies are investing in big data initiatives to help them predict consumer behavior. Knowing the most effective ways to mine social media data can help you acquire information that generates amazing business results. Social media is unstructured, dynamic, and future-oriented. Effective, insightful data mining requires new analytical tools and techniques. Written by experts at social networking companies, Social Media Data Mining and Analytics provides a hands-on course that teaches you how to use state-of-the-art tools and sophisticated data mining techniques specifically geared to social media. It digs deeply into the mechanics of collecting and applying social media data to understand customers, define trends, and make predictions that can improve analytics for growth and sales. "--Amazon.com

Cataloging source

UKMGB

Dewey number

658.8/3402856312

Illustrations

illustrations

Index

index present

LC call number

HF5415.32

LC item number

.S93 2019

Literary form

non fiction