This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, "see" analysis strategies, and assist in the development and writing of research reports.

This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, “see” analysis strategies, and assist in the development and writing of research reports.

Rachel Dorothy Tanur (1958-2002) wasn't trained as a social scientist, but she cared deeply about people and their lives and was an acute observer of living conditions and interactions. Her profound empathy for others and her commitment to helping those less fortunate than herself accompanied her on her travels and often guided her photography. She delighted in capturing the interaction between people and the artifacts they created and used, which, of course, are the raw materials of social science. In 1999 Tanur was diagnosed with cancer, and in response, she made several trips to Cuba, South and Central America, Africa, and Europe, as well as across the United States, before her death at the age of 43. The following year, Tanur's family and friends organized a memorial exhibit at Gilda's Club in New York called Cancer Journeys. The Social Science Research Council then opened its space for second show entitled Photographic Journeys. When Nikita Pokrovsky of Moscow's State University-Higher School of Economics experienced the SSRC exhibit, he was struck by the "human passion and compassion" of Tanur's work. He suggested combining the photographs with commentary, transforming the photos into useful tools for visual social science. These commentaries, written by an international group of social scientists, now accompany close to fifty of Rachel's photographs, and together the exhibit made its debut at the National Science Foundation in their Art of Science's 2006 show, Visualizing Social Science. This volume is an extension of that exhibition.

The representation of abstract data and ideas can be a difficult and tedious task to handle when learning new concepts; however, the advances in emerging technology have allowed for new methods of representing such conceptual data. Information Visualization Techniques in the Social Sciences and Humanities is a critical scholarly resource that examines the application of information visualization in the social sciences and humanities. Featuring coverage on a broad range of topics such as social network analysis, complex systems, and visualization aesthetics, this book is geared towards professionals, students, and researchers seeking current research on information visualization.

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

An excellent resource for social studies teachers, this book will help them learn about and reflect on their responsibilities in our society. It focuses on classroom-based experiences and real-world contexts. The teaching methods discussed are also closely associated to social studies subject matter so they can be integrated into the actual classroom. Each chapter also examines how social studies is situated within the larger elementary curriculum to demonstrate the interdisciplinary nature of the instruction.