Social Media Analytics: Techniques and Insights for Extracting Business Value Out of Social Media

About

Features

• Teaches cutting-edge techniques for unstructured data identification, analysis, and interpretation
• Gives expert advice for avoiding costly pitfalls in social media analytics
• Includes three chapter-length case study projects
• Written by leaders of IBM's pioneering Social Media Analysis Initiative



Description

• Copyright 2016
• Dimensions: 6" x 9"
• Pages: 304
• Edition: 1st

• Book
• ISBN-10: 0-13-389256-5
• ISBN-13: 978-0-13-389256-7

Transform Raw Social Media Data into Real Competitive Advantage

There’s real competitive advantage buried in today’s deluge of social media data. If you know how to analyze it, you can increase your relevance to customers, establishing yourself as a trusted supplier in a cutthroat environment where consumers rely more than ever on “public opinion” about your products, services, and experiences.

Social Media Analytics is the complete insider’s guide for all executives and marketing analysts who want to answer mission-critical questions and maximize the business value of their social media data. Two leaders of IBM’s pioneering Social Media Analysis Initiative offer thorough and practical coverage of the entire process: identifying the right unstructured data, analyzing it, and interpreting and acting on the knowledge you gain.

Their expert guidance, practical tools, and detailed examples will help you learn more from all your social media conversations, and avoid pitfalls that can lead to costly mistakes.

You’ll learn how to:

• Focus on the questions that social media data can realistically answer
• Determine which information is actually useful to you—and which isn’t
• Cleanse data to find and remove inaccuracies
• Create data models that accurately represent your data and lead to more useful answers
• Use historical data to validate hypotheses faster, so you don’t waste time
• Identify trends and use them to improve predictions
• Drive value “on-the-fly” from real-time/ near-real-time and ad hoc analyses
• Analyze text, a.k.a. “data at rest”
• Recognize subtle interrelationships that impact business performance
• Improve the accuracy of your sentiment analyses
• Determine eminence, and distinguish “talkers” from true influencers
• Optimize decisions about marketing and advertising spend

Whether you’re a marketer, analyst, manager, or technologist, you’ll learn how to use social media data to compete more effectively, respond more rapidly, predict more successfully…grow profits, and keep them growing.



Sample Content

Sample Pages

Download the sample pages (includes Chapter 3 and Index)

Table of Contents

Foreword    xviii

Preface: Mining for Gold (or Digging in the Mud)    xx

Just What Do We Mean When We Say Social Media?    xx

Why Look at This Data?    xxi

How Does This Translate into Business Value?    xxii

The Book’s Approach    xxiv

Data Identification    xxiv

Data Analysis    xxv

Information Interpretation    xxvi

Why You Should Read This Book    xxvii

What This Book Does and Does Not Focus On    xxix

Acknowledgments    xxxi

Matt Ganis    xxxi

Avinash Kohirkar    xxxi

Joint Acknowledgments    xxxii

About the Authors    xxxiv

Part I: Data Identification

Chapter 1: Looking for Data in All the Right Places    1

What Data Do We Mean?    2

What Subset of Content Are We Interested In?    4

Whose Comments Are We Interested In?    6

What Window of Time Are We Interested In?    7

Attributes of Data That Need to Be Considered    7

Structure    8

Language    9

Region    9

Type of Content    10

Venue    13

Time    14

Ownership of Data    14

Summary    15

Chapter 2: Separating the Wheat from the Chaff    17

It All Starts with Data    18

Casting a Net    19

Regular Expressions    23

A Few Words of Caution    27

It’s Not What You Say but WHERE You Say It    28

Summary    29

Chapter 3: Whose Comments Are We Interested In?    31

Looking for the Right Subset of People    32

Employment    32

Sentiment    32

Location or Geography    33

Language    33

Age    34

Gender    34

Profession/Expertise    34

Eminence or Popularity    35

Role    35

Specific People or Groups    35

Do We Really Want ALL the Comments?    35

Are They Happy or Unhappy?    37

Location and Language    39

Age and Gender    41

Eminence, Pr



Updates

Submit Errata

