Books in the Behaviormetrics: Quantitative Approaches to Human Behavior series

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures.Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.

The purpose of this book is to thoroughly prepare the reader for applied research in clustering. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses.

This book focuses on a development for assessing mental changes using eye pupil reactions, namely extracting emotional change from the response to evaluate the viewer's interest in visual information.

This book first presents an overview of the history of a national character survey by the Institute of Statistical Mathematics that has been conducted for more than 65 years. The Japanese National Character Survey, launched in 1953, is a rare longitudinal survey in the world of survey research based on rigorous statistical sampling theory, motivating other countries to launch similar longitudinal surveys, including the General Social Survey (GSS), the Allgemeine Bevölkerungsumfrage der Sozialwissenschaften (ALLBUS, German General Social Survey (GGSS)), Eurobarometer, and others. Since the early 1970s, the Japanese survey has been extended as a cross-national survey for more advanced research of the Japanese national character in a comparative context. Second, the book explains the paradigm of cross-national studies called the Cultural Manifold Analysis (CULMAN), developed in the longitudinal and cross-national surveys, with practical examples of analysis. This explanation will helphelps a wide range of readers to better understand the cross-national comparative surveys of attitudes, opinion, and social values as basic information for evidence-based policymaking and research.

This book brings together two major trends: data science and blockchains. It is one of the first books to systematically cover the analytics aspects of blockchains, with the goal of linking traditional data mining research communities with novel data sources. Data science and big data technologies can be considered cornerstones of the data-driven digital transformation of organizations and society. The concept of blockchain is predicted to enable and spark transformation on par with that associated with the invention of the Internet. Cryptocurrencies are the first successful use case of highly distributed blockchains, like the world wide web was to the Internet. The book takes the reader through basic data exploration topics, proceeding systematically, method by method, through supervised and unsupervised learning approaches and information visualization techniques, all the way to understanding the blockchain data from the network science perspective. Chapters introduce the cryptocurrency blockchain data model and methods to explore it using structured query language, association rules, clustering, classification, visualization, and network science. Each chapter introduces basic concepts, presents examples with real cryptocurrency blockchain data and offers exercises and questions for further discussion. Such an approach intends to serve as a good starting point for undergraduate and graduate students to learn data science topics using cryptocurrency blockchain examples. It is also aimed at researchers and analysts who already possess good analytical and data skills, but who do not yet have the specific knowledge to tackle analytic questions about blockchain transactions. The readers improve their knowledge about the essential data science techniques in order to turn mere transactional information into social, economic, and business insights.