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Twitter Data Analytics

Language EnglishEnglish
Book Paperback
Book Twitter Data Analytics Shamanth Kumar
Libristo code: 02093927
Publishers Springer-Verlag New York Inc., November 2013
This brief provides methods for harnessing Twitter data to discover solutions to complex inquiries.... Full description
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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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About the book

Full name Twitter Data Analytics
Author Shamanth Kumar, Fred Morstatter, Huan Liu
Language English
Binding Book - Paperback
Date of issue 2013
Number of pages 77
EAN 9781461493716
ISBN 1461493714
Libristo code 02093927
Publishers Springer-Verlag New York Inc.
Weight 1474
Dimensions 155 x 235 x 6

Categories

Technology, Engineering, Agriculture > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
Computing & Information Technology > Computer science > Artificial intelligence > Expert systems / knowledge-based systems
Computing & Information Technology > Computer science > Human–computer interaction > User interface design & usability
Computing & Information Technology > Computer programming / software engineering > Database programming
Computing & Information Technology > Databases > Data capture & analysis
Computing & Information Technology > Databases > Data mining
Computing & Information Technology > Graphical & digital media applications
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