Andrea Fronzetti Colladon – författare

Social Network Analysis and Text Mining for Big Data presents cutting-edge methods and tools that bridge the gap between text mining and social network analysis research while also providing new insights for analyzing (big) textual and network data. These tools are designed to cater to the needs of both business analysts and researchers to facilitate the creation of groundbreaking analytics.

Beginning with clear definitions of social network analysis and text mining, this book benefits from a thoughtfully curated selection of methods and tools, drawn from the authors’ extensive research in the field. The focus then shifts to demonstrate how the interplay between words and networks can unlock the full potential of big data analytics. A centerpiece of the book is the Semantic Brand Score (SBS), a versatile and powerful metric for assessing brand importance through text analysis. All of the above is corroborated and illustrated with practical applications and case studies showing the value of these analytics in supporting change and improved managerial decisions. It also introduces a specialized software tool which enables users to perform the analyses detailed in the text.

This book is a must-read for business leaders, marketing professionals, policymakers, researchers, and university students. It offers practical insights and actionable advice for achieving increased performance of companies and societal actions. The writing is tailored to make complex concepts accessible to both experienced researchers and readers who are new to the field.

Social Network Analysis and Text Mining for Big Data presents cutting-edge methods and tools that bridge the gap between text mining and social network analysis research while also providing new insights for analyzing (big) textual and network data. These tools are designed to cater to the needs of both business analysts and researchers to facilitate the creation of groundbreaking analytics.

Beginning with clear definitions of social network analysis and text mining, this book benefits from a thoughtfully curated selection of methods and tools, drawn from the authors’ extensive research in the field. The focus then shifts to demonstrate how the interplay between words and networks can unlock the full potential of big data analytics. A centerpiece of the book is the Semantic Brand Score (SBS), a versatile and powerful metric for assessing brand importance through text analysis. All of the above is corroborated and illustrated with practical applications and case studies showing the value of these analytics in supporting change and improved managerial decisions. It also introduces a specialized software tool which enables users to perform the analyses detailed in the text.

This book is a must-read for business leaders, marketing professionals, policymakers, researchers, and university students. It offers practical insights and actionable advice for achieving increased performance of companies and societal actions. The writing is tailored to make complex concepts accessible to both experienced researchers and readers who are new to the field.

Chapters span disciplinary boundaries, covering both computer science and AI, as well as sociology and psychology, to encompass all aspects of social computing as an emerging field. They also examine the complexity of social networks and algorithmic decision-making whilst drawing on case studies from diverse industries and exploring important issues, such as the ethical implications of AI, data privacy regulation, and safe data sharing. Ultimately, this Handbook illustrates the diverse ways in which digital technologies can be used to analyze social behavior, recognise individual and group interaction patterns, and improve daily life.

Providing a comprehensive overview of the latest developments in social computing, this Handbook will be an essential read for students and scholars of human dynamics, social network analysis, and sociology. It will also be an invaluable guide for professionals seeking a deeper understanding of how technology can be used to analyze social dynamics.