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Quantitative methods in social research --- Dyadic analysis (Social sciences) --- Analyse dyadique (Sciences sociales) --- #SBIB:303H520 --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Dyadic analysis (Social sciences). --- Dyadic data analysis (Social sciences) --- Sociometry
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"We demonstrate and develop dyadic-probabilistic methods in connection with non-homogeneous bilinear operators, namely singular integrals and square functions. We develop the full non-homogeneous theory of bilinear singular integrals using a modern point of view. The main result is a new global Tb theorem for Calderon-Zygmund operators in this setting. Our main tools include maximal truncations, adapted Cotlar type inequalities and suppression and big piece methods. While proving our bilinear results we also advance and refine the linear theory of Calderon-Zygmund operators by improving techniques and results. For example, we simplify and make more efficient some non-homogeneous summing arguments appearing in T1 type proofs. As a byproduct, we can manage with ease quite general modulus of continuity in the kernel estimates. Our testing conditions are also quite general by virtue of the big piece method of proof"--
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Quantitative methods in social research --- Dyadic analysis (Social sciences) --- Human behavior --- Psychometrics --- Sociometry --- Educational tests and measurements --- Mathematical sociology --- Social interaction --- Social psychology --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Human behavior models --- Dyadic data analysis (Social sciences) --- Mathematical models --- Measurement --- Scaling --- Methodology
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"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"--
Dyadic analysis (Social sciences) --- Online social networks --- Social sciences --- Webometrics. --- Bibliometry, Web --- Cybermetrics --- Internetometrics --- Metrics, Web --- Netometrics --- Web bibliometry --- Web metrics --- Webometry --- Quantitative research --- World Wide Web --- Electronic social networks --- Social networking Web sites --- Virtual communities --- Social media --- Social networks --- Sociotechnical systems --- Web sites --- Dyadic data analysis (Social sciences) --- Sociometry --- Research. --- Research --- Methodology. --- Twitter. --- Communities, Online (Online social networks) --- Communities, Virtual (Online social networks) --- Online communities (Online social networks) --- Online social networks - Research --- Social sciences - Research - Methodology --- Webometrics --- X (Social networking service)
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