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Social Media Analytics: Techniques and Insights for Extracting Business Value Out of Social Media
- By Matthew Ganis, Avinash Kohirkar
- Published Dec 11, 2015 by IBM Press. Part of the IBM Press series.
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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
Online Sample Chapter
Social Media Analytics: Whose Comments Are We Interested In?
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
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