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Kirjailija

Craig M. Rawlings

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuodelta 2023, suosituimpiin kuuluu Network Analysis. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Network Analysis

Network Analysis

Craig M. Rawlings; Jeffrey A. Smith; James Moody; Daniel A. McFarland

Cambridge University Press
2023
pokkari
The size and availability of network information has exploded over the last decade. Social scientists now share the stage of network analysis with computer scientists, physicists, and statisticians. While a number of introductions to network analysis are now available, most focus on theory, methods, or application alone. This book integrates all three. Network Analysis is an introduction to both the why and how of Social Network Analysis (SNA). It presents a broad theoretical overview rooted in social scientific approaches and guides users in how network analysis can answer core theoretical questions. It provides a comprehensive overview of descriptive and analytical approaches, including practical tutorials in R with sample data sets. Using an integrated approach, this book aims to quickly bring novice network researchers up to speed while avoiding common programming and analysis mistakes so that they might gain insight into the fundamental theories, key concepts, and methodological application of SNA.
Network Analysis

Network Analysis

Craig M. Rawlings; Jeffrey A. Smith; James Moody; Daniel A. McFarland

Cambridge University Press
2023
sidottu
The size and availability of network information has exploded over the last decade. Social scientists now share the stage of network analysis with computer scientists, physicists, and statisticians. While a number of introductions to network analysis are now available, most focus on theory, methods, or application alone. This book integrates all three. Network Analysis is an introduction to both the why and how of Social Network Analysis (SNA). It presents a broad theoretical overview rooted in social scientific approaches and guides users in how network analysis can answer core theoretical questions. It provides a comprehensive overview of descriptive and analytical approaches, including practical tutorials in R with sample data sets. Using an integrated approach, this book aims to quickly bring novice network researchers up to speed while avoiding common programming and analysis mistakes so that they might gain insight into the fundamental theories, key concepts, and methodological application of SNA.