• Title Twitter Data Analytics
• Author(s) Shamanth Kumar, Fred Morstatter, Huan Liu
• Publisher: Springer; 2014 edition (November 25, 2013); eBook(Preprint)
• Permission: Download the Preprint at Book's Homepage
• Paperback 87 pages
• eBook PDF (89 pages, 3.3 MB)
• Language: English
• ISBN-10: 1461493714
• ISBN-13: 978-1461493716
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Book Description

This book provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter's APIs and offers strategies for curating large datasets.

The book gives examples of Twitter data with real-world examples, the present challenges and complexities of building visual analytic tools, and the best strategies to address these issues. Examples demonstrate how powerful measures can be computed using various Twitter data sources. Due to its openness in sharing data, Twitter is a prime example of social media in which researchers can verify their hypotheses, and practitioners can mine interesting patterns and build their own applications.

This book is designed to provide researchers, practitioners, project managers, as well as graduate students with an entry point to jump start their Twitter endeavors. It also serves as a convenient reference for readers seasoned in Twitter data analysis.

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• Data Analysis and Data Mining
• Algorithms and Data Structures
• Statistics, R Language and SAS Programming
• Probability, Stochastic Process, Queueing Theory, etc.

• Twitter Data Analytics (Shamanth Kumar, et al)
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