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.

Andrea Fronzetti Colladon is an Associate Professor of Business Management and Analytics at Roma Tre University in Italy.

Roberto Vestrelli is a PhD Candidate in Industrial and Information Engineering at the University of Perugia, Italy.