Doing computational social science a practical introduction / John McLevey.
| Author/creator | McLevey, John |
| Format | Electronic |
| Publication Info | Los Angeles : SAGE, [2022] |
| Description | xv, 667 pages : illustrations ; 25 cm |
| Supplemental Content | Full text available from SAGE Research Methods Core |
| Subjects |
| Abstract | "Computational approaches offer exciting opportunities for us to do social science differently. This beginner's guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach, including machine learning and social network analysis, in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Teaches you good habits and working practices that enable you to do programming well. This book is for anyone who wants to use computational methods to conduct a social science research project. Supported by a wealth of online resources, including video tutorials and datasets for practice so you can learn at your own pace, this book equips you with the skills to conduct computational social science research for the first time, with confidence"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references (pages 644-655) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2021937242 |
| ISBN | 9781526468185 (paperback) |
| ISBN | 9781526468192 (hardcover) |
| ISBN | (epub) |
| ISBN | (epub) |
| ISBN | (pdf) |