9780133892567

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.

Dr. Matthew Ganis, a member of IBM’s Academy of Technology, is currently an IBM Senior Technical Staff Member located in Somers, New York. His current areas of interest include social media analytics, the Internet of Things, and Agile software methodologies. He is an adjunct professor of computer science and astronomy at Pace University in Pleasantville, New York, where he teaches at both the undergraduate and graduate level.

Dr. Ganis holds a BS degree in computer science and an MBA in information systems from Pace University, an MS degree in astronomy from the University of Western Sydney, Australia, and a doctorate of professional studies in computing from Pace University. He has authored or co-authored over 40 papers in both of his fields of interest, ranging from programming techniques, computer system administration, computer networking, and topics on stellar evolution and radio astronomy. He is also the proud coauthor of A Practical Guide to Distributed Scrum published by IBM Press.

In his 30-year career at IBM, he has been responsible for a number of technological advances such as the creation of the first enterprise firewalls for IBM; the creation of highly available World Wide Web platforms to support the Atlanta, Sydney, and Nagano Olympics (which secured Dr. Ganis and his team a spot in the Guinness Book of World Records for the highest sustained rate of Internet web traffic); and the proliferation of advanced software development techniques across IBM’s worldwide development laboratories.

He can be found on LinkedIn (https://www.linkedin.com/in/mattganis), on Twitter as @mattganis, or on his blog at http://mganis.blogspot.com.

Avinash Kohirkar is currently Manager of Social Business Adoption in IBM. His current areas of interest include deployment and adoption of social technologies within an enterprise, social engagement dashboards, and social media analytics. Avinash Kohirkar holds a BS degree in electronics and communications engineering from Osmania University (India), an MS degree in industrial engineering from NITIE (India), and an MBA in finance from California State University. He has contributed to IBM white papers and has given numerous presentations on social analytics in IBM and outside IBM. He has authored a number of articles on this subject that have been published in the Cutter IT Journal and Infosys Lab Briefings.

In his 19-year career at IBM, he has leveraged technologies such as e-business, Web 2.0, social collaboration, social graph technologies, big data, and social media and text analytics for the business benefit of IBM and IBM’s customers. He is recognized as a thought leader in the project management profession within IBM and is certified as Executive Project Manager at the highest level within IBM. He has held several technical, business, and management positions during his career: Architect, Development Manager, Project Manager, Project Executive, Associate Partner, Project Executive, and Business Manager.

He can be found on LinkedIn (https://www.linkedin.com/in/ AvinashKohirkar) and on Twitter as @kohirkar.

Section 1. Data Identification
1. Introduction to Data Identification
2. What?
3. Who?
4. When?
5. Where?

Section 2. Data Analysis
6. Introduction to Data Analysis
7. Validating Your Hypothesis
8. Real Time Analysis
9. Ad Hoc Exploration
10. Deep Analysis
11. Social Media and Text Analysis (Data at Rest)

Section 3. Information Interpretation
12. Introduction
13. State of the Art in "Insights"
14. Sentiment Accuracy

Appendices
A. Case Study 1
B. Case Study 2
C. Case Study 3

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

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

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

0133892565

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