Twitter: A Digital Socioscope
By Yelena Mejova, Ingmar Weber, Michael W. Macy. 2015
85 citations recorded by the source corpus.
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.
Subfields: Statistical and Nonlinear Physics
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In Statistical and Nonlinear Physics
Citations in the corpus
- SemEval-2016 Task 4: Sentiment Analysis in Twitter (2016, methodology): “Classifying tweets according to sentiment has many applications in political science, social sciences, market research, and many others (Martı́nezCámara et al., 2014; Mejova et al., 2015).”
- From classification to quantification in tweet sentiment analysis (2016, background): “…has become a ubiquitous enabling technology in the Twit-tersphere, since classifying tweets according to the sentiment they convey towards a given entity has many applications in political science, social science, market research, and many others (Martı´nez-Ca´mara et al. 2014; Mejova et al. 2015).”