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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.
Laboratory Experiments in the Social Sciences is the only book providing core information for researchers about the ways and means to conduct experiments. Its comprehensive regard for laboratory experiments encompasses “how-to explanations, investigations of philosophies and ethics, explorations of experiments in specific social science disciplines, and summaries of both the history and future of social science laboratories. No other book offers such a direct avenue to enlarging our knowledge in the social sciences.This collection of original chapters combines instructions and advice about the design of laboratory experiments in the social sciences with the array of other issues. While there are books on experimental design and chapters in more general methods books on design, theory, and ethical issues, no other book attempts to discuss the fundamental ideas of the philosophy of science or lays out the methods comprehensively or in such detail. Experimentation has recently prospered because of increasing interest in cross-disciplinary syntheses, and this book of advice, guidelines, and observations underline its potential and increasing importance. · Provides a comprehensive summary of issues in social science experimentation, from ethics to design, management, and financing· Offers "how-to" explanations of the problems and challenges faced by everyone involved in social science experiments· Pays attention to both practical problems and to theoretical and philosophical arguments· Defines commonalities and distinctions within and among experimental situations across the social sciences
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.
The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences. The data revolution in social science research has not only produced new business models, but has also provided policymakers with better decision-making support tools. In this volume, statisticians, computer scientists and experts on social research discuss the opportunities and challenges of the social data revolution in order to pave the way for addressing new research problems. The respective contributions focus on complex social systems and current methodological advances in extracting social knowledge from large data sets, as well as modern social research on human behavior and society using large data sets. Moreover, they analyze integrated systems designed to take advantage of new social data sources, and discuss quality-related issues. The papers were originally presented at the 2nd International Conference on Data Science and Social Research, held in Milan, Italy, on February 4-5, 2019.
Some in the social sciences argue that the same logic applies to both qualitative and quantitative methods. In A Tale of Two Cultures, Gary Goertz and James Mahoney demonstrate that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. They identify and discuss major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, Goertz and Mahoney also seek to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. This book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.
Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries
This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.
Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.