A resource for social scientists on how Twitter data can be used to study individual behavior and social interaction.
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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 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 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.
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Paperback octavo, very good condition, minimal edgewear. 173 pp. How can Twitter data be used to study individual human behavior and social interaction globally? This edited book of essays introduces readers to the methods, opportunities, and challenges of using Twitter data, ranging from the number of people infected by the flu, to national elections, to 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. These case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. N° de réf. du vendeur 23590
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