Twitter :
Twitter : a digital socioscope /
edited by Yelena Mejova, Qatar Computing Research Institute, Ingmar Weber, Qatar Computing Research Institute, Michael W. Macy, Cornell University, Itha, New York.
- Cambridge : Cambridge University Press, 2015.
- 1 online resource (x, 173 pages) : digital, PDF file(s).
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Introduction / Analyzing Twitter data / Political opinion / Socioeconomic indicators / Hyperlocal happiness from tweets / Public health / Disaster monitoring / Scott A. Golder and Michael W. Macy -- Shamanth Kumar, Fred Morstatter, and Huan Liu -- Daniel Gayo-Avello -- Huina Mao -- Daniele E. Quercia -- Patty Kostkova -- Bella Robinson, Robert Power, and Mark Cameron. 1. 2. 3. 4. 5. 6.
How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.
9781316182635 (ebook)
Twitter.
Dyadic data analysis (Social sciences)
Webometrics.
Social sciences--Research--Methodology.
Online social networks--Research.
HM533.5 / .T95 2015
302.34072/7
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Introduction / Analyzing Twitter data / Political opinion / Socioeconomic indicators / Hyperlocal happiness from tweets / Public health / Disaster monitoring / Scott A. Golder and Michael W. Macy -- Shamanth Kumar, Fred Morstatter, and Huan Liu -- Daniel Gayo-Avello -- Huina Mao -- Daniele E. Quercia -- Patty Kostkova -- Bella Robinson, Robert Power, and Mark Cameron. 1. 2. 3. 4. 5. 6.
How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.
9781316182635 (ebook)
Twitter.
Dyadic data analysis (Social sciences)
Webometrics.
Social sciences--Research--Methodology.
Online social networks--Research.
HM533.5 / .T95 2015
302.34072/7