Logo - springer
Slogan - springer

Computer Science - Database Management & Information Retrieval | Twitter Data Analytics

Twitter Data Analytics

Kumar, Shamanth, Morstatter, Fred, Liu, Huan

2014, X, 77 p. 26 illus.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$39.99

(net) price for USA

ISBN 978-1-4614-9372-3

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase


learn more about Springer eBooks

add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$54.99

(net) price for USA

ISBN 978-1-4614-9371-6

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

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.

Content Level » Research

Keywords » Big data - Data mining - Social media - Twitter analytics - Visual analytics

Related subjects » Artificial Intelligence - Database Management & Information Retrieval - HCI - Information Systems and Applications

Table of contents 

Introduction.- Crawling Twitter Data.- Storing Twitter Data.- Analyzing Twitter Data.- Visualizing Twitter Data.

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Data Mining and Knowledge Discovery.