Twitter: A Digital Socioscope
- 3h 30m
- Ingmar Weber, Michael W. Macy, Yelena Mejova
- Cambridge University Press
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.
- Features clearly written and technically accessible case studies on a wide range of important topics that are frequently featured in the popular press
- Provides a balanced assessment of the advantages and disadvantages of using Twitter to make predictions and analyze data
About the Editors
Yelena Mejova, Qatar Computing Research Institute
Yelena Mejova is a scientist in the Social Computing Group at Qatar Computing Research Institute. Before QCRI, Yelena was a postdoc at Yahoo! Research in Barcelona. A part of the Web Mining Group, her work concerned building semantically enriched information retrieval systems, as well as examining user behavior through social media. Prior to that, her PhD thesis at the University of Iowa concerned the design and application of sentiment analysis tools for mining a variety of social media discourses, including political speech.
Ingmar Weber, Qatar Computing Research Institute
Ingmar Weber is a senior scientist in the Social Computing group at Qatar Computing Research Institute. As an undergraduate he studied mathematics at the University of Cambridge, before moving to the Max Planck Institute for Computer Science, Germany, for his PhD. Before moving to Qatar, he spent two years working at the École Polytechnique Fédérale de Lausanne, Switzerland, and three years at Yahoo! Research in Barcelona, Spain.
Michael W. Macy, Cornell University, New York
Michael Macy is Goldwin Smith Professor of Arts and Sciences and Director of the Social Dynamics Laboratory at Cornell University. His research team has used computational models, online experiments, and data from social media to explore enigmatic social patterns, the emergence and collapse of fads, the spread of self-destructive behaviors, cooperation in social dilemmas, the critical mass in collective action, the spread of contagion's on small world networks, the polarization of opinion, segregation of neighborhoods, and assimilation of minority cultures.
In this Book
Analyzing Twitter Data
Hyperlocal Happiness from Tweets