1 option
Twitter Data Analytics / by Shamanth Kumar, Fred Morstatter, Huan Liu.
- Format:
- Book
- Author/Creator:
- Kumar, Shamanth, author.
- Morstatter, Fred, author.
- Liu, Huan, author.
- Series:
- Computer Science (Springer-11645)
- SpringerBriefs in computer science 2191-5768
- SpringerBriefs in Computer Science, 2191-5768
- Language:
- English
- Subjects (All):
- Data mining.
- Multimedia systems.
- User interfaces (Computer systems).
- Artificial intelligence.
- Database management.
- Data Mining and Knowledge Discovery.
- Multimedia Information Systems.
- User Interfaces and Human Computer Interaction.
- Artificial Intelligence.
- Database Management.
- Local Subjects:
- Data Mining and Knowledge Discovery.
- Multimedia Information Systems.
- User Interfaces and Human Computer Interaction.
- Artificial Intelligence.
- Database Management.
- Physical Description:
- 1 online resource (X, 77 pages) : 26 illustrations.
- Edition:
- First edition 2014.
- Contained In:
- Springer eBooks
- Place of Publication:
- New York, NY : Springer New York : Imprint: Springer, 2014.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- Introduction
- Crawling Twitter Data
- Storing Twitter Data
- Analyzing Twitter Data
- Visualizing Twitter Data.
- Other Format:
- Printed edition:
- ISBN:
- 978-1-4614-9372-3
- 9781461493723
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.