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About this book
This brief 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 text 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 brief 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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Table of contents (5 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Twitter Data Analytics
Authors: Shamanth Kumar, Fred Morstatter, Huan Liu
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-1-4614-9372-3
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2014
Softcover ISBN: 978-1-4614-9371-6Published: 12 November 2013
eBook ISBN: 978-1-4614-9372-3Published: 11 November 2013
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: X, 77
Number of Illustrations: 26 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Multimedia Information Systems, User Interfaces and Human Computer Interaction, Artificial Intelligence, Database Management