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" Social media data mining and analytics / "
Gabor Szabo, Gungor Polatkan, Oscar Boykin, Antonios Chalkiopoulos.
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BL
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| Record Number
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839845
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| Main Entry
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Szabó, Gábor
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| Title & Author
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Social media data mining and analytics /\ Gabor Szabo, Gungor Polatkan, Oscar Boykin, Antonios Chalkiopoulos.
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| Publication Statement
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Indianapolis, IN :: John Wiley & Sons,, [2019]
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| Page. NO
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1 online resource (xxxv, 316 pages) :: illustrations (some color)
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| ISBN
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111882489X
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: 1118824903
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: 1119183510
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: 9781118824894
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: 9781118824900
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: 9781119183518
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1118824857
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9781118824856
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| Notes
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Includes index.
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| Contents
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Introduction -- Chapter 1. Users: The Who of Social Media -- Chapter 2. Networks: The How of Social Media -- Chapter 3. Temporal Processes: The When of Social Media -- Chapter 4. Content: The What of Social Media -- Chapter 5. Processing Large Datasets -- Chapter 6. Learn, Map, and Recommend -- Chapter 7. Conclusions.
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| Abstract
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Harness the power of social media to predict customer behavior and improve sales. Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in big data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses.Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, Live Journal, movie reviews, and other rich data sources. In it, you will learn:The four key characteristics of online services-users, social networks, 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 How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.
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Business planning-- Data processing.
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Consumer behavior-- Forecasting.
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Consumer profiling-- Data processing.
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Data mining-- Social aspects.
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Data mining.
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Social media-- Data processing.
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BUSINESS ECONOMICS-- Industrial Management.
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BUSINESS ECONOMICS-- Management Science.
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BUSINESS ECONOMICS-- Management.
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BUSINESS ECONOMICS-- Organizational Behavior.
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Business planning-- Data processing.
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Consumer behavior-- Forecasting.
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Data mining-- Social aspects.
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Data mining.
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| Dewey Classification
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658.8/3402856312
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| LC Classification
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HF5415.32.S93 2019eb
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| Added Entry
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Boykin, Oscar
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Chalkiopoulos, Antonios
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Polatkan, Gungor
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