Twitter data analytics / / Shamanth Kumar, Fred Morstatter, Huan Liu

• Autore: Kumar Shamanth
• Pubblicazione: New York : , : Springer, , 2014
• Edizione: 1st ed. 2014.
• Descrizione fisica: 1 online resource (x, 77 pages) : illustrations (some color), color maps
• Disciplina: 006.312
• Soggetto topico: Data mining
• Persona (resp. second.): MorstatterFred; LiuHuan <1958->
• Note generali: "ISSN: 2191-5768."
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Introduction -- Crawling Twitter data -- Storing Twitter data -- Analyzing Twitter data -- Visualizing Twitter data.
• Sommario/riassunto: 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.
• Titolo autorizzato: Twitter Data Analytics
• ISBN: 1-4614-9372-2
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910299049603321
• Lo trovi qui: Univ. Federico II
• Serie: SpringerBriefs in computer science.