Although written simply enough to be accessible to undergraduates, accomplished scholars are likely to appreciate it too. Reading it taught me quite a lot about a subject I thought I knew rather well. - Paul Vogt, Illinois State University "This book brings the art and science of building and applying innovative online research tools to students and faculty across the social sciences." - William H. Dutton, University of Oxford A comprehensive guide to the theory and practice of web Social Science. This book demonstrates how the web is being used to collect social research data, such as online surveys and interviews, as well as digital trace data from social media environments, such as Facebook and Twitter. It also illuminates how the advent of the web has led to traditional social science concepts and approaches being combined with those from other scientific disciplines, leading to new insights into social, political and economic behaviour. Situating social sciences in the digital age, this book aids: understanding of the fundamental changes to society, politics and the economy that have resulted from the advent of the web choice of appropriate data, tools and research methods for conducting research using web data learning how web data are providing new insights into long-standing social science research questions appreciation of how social science can facilitate an understanding of life in the digital age It is ideal for students and researchers across the social sciences, as well as those from information science, computer science and engineering who want to learn about how social scientists are thinking about and researching the web.

This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Recently, social science has had numerous episodes of influential research that was found invalid when placed under rigorous scrutiny. The growing sense that many published results are potentially erroneous has made those conducting social science research more determined to ensure the underlying research is sound. Transparent and Reproducible Social Science Research is the first book to summarize and synthesize new approaches to combat false positives and non-reproducible findings in social science research, document the underlying problems in research practices, and teach a new generation of students and scholars how to overcome them. Understanding that social science research has real consequences for individuals when used by professionals in public policy, health, law enforcement, and other fields, the book crystallizes new insights, practices, and methods that help ensure greater research transparency, openness, and reproducibility. Readers are guided through well-known problems and are encouraged to work through new solutions and practices to improve the openness of their research. Created with both experienced and novice researchers in mind, Transparent and Reproducible Social Science Research serves as an indispensable resource for the production of high quality social science research.

"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--

This highly original work presents laboratory science in a deliberately skeptical way: as an anthropological approach to the culture of the scientist. Drawing on recent work in literary criticism, the authors study how the social world of the laboratory produces papers and other "texts,"' and how the scientific vision of reality becomes that set of statements considered, for the time being, too expensive to change. The book is based on field work done by Bruno Latour in Roger Guillemin's laboratory at the Salk Institute and provides an important link between the sociology of modern sciences and laboratory studies in the history of science.

The impact agenda is set to shape the way in which social scientists prioritise the work they choose to pursue, the research methods they use and how they publish their findings over the coming decade, but how much is currently known about how social science research has made a mark on society? Based on a three year research project studying the impact of 360 UK-based academics on business, government and civil society sectors, this groundbreaking new book undertakes the most thorough analysis yet of how academic research in the social sciences achieves public policy impacts, contributes to economic prosperity, and informs public understanding of policy issues as well as economic and social changes. The Impact of the Social Sciences addresses and engages with key issues, including: identifying ways to conceptualise and model impact in the social sciences developing more sophisticated ways to measure academic and external impacts of social science research explaining how impacts from individual academics, research units and universities can be improved. This book is essential reading for researchers, academics and anyone involved in discussions about how to improve the value and impact of funded research.

Are human beings less violent than before? Why do we adopt certain moral and political judgements? Why is the gap between rich and poor getting bigger? How do we decide which criminal policies are effective? What is the Population Challenge for the 21st Century? What is social science? In Big Ideas in Social Science, David Edmonds and Nigel Warburton put these and more of our society’s burning questions to 18 of the world’s leading social scientists including Steven Pinker, Ann Oakley, Lawrence Sherman, Kate Pickett, Robert J. Shiller and Doreen Massey. The result is a collection of thought-provoking discussions that span the fields of sociology, politics, economics, criminology, geography and many more.From the people who brought us the Philosophy Bites series, Big Ideas in Social Science is a fascinating and accessible introduction to the key ideas and findings of the social sciences. The interviews for this book are based on a series of podcasts, Social Science Bites, sponsored by SAGE. Social Science Bites was inspired by the popular Philosophy Bites podcast (www.philosophybites.com), which was founded by David and Nigel in 2007 and has so far had 26 million downloads. Philosophy Bites has spawned three books, Philosophy Bites, Philosophy Bites Back and Philosophy Bites Again.

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--