This book adds two key components critical for social science students that are often lacking in other texts. The first is a discussion of key computing components starting at the most basic – often these steps are overlooked in texts written for computer science students. Second is the excellent grounding in and integration with social science theory and concepts.
McLevey has provided us with a book that clearly imparts the technical skills of computational methods, but crucially he has done so in a way that accessibly embeds them in a social science context. Whilst we’ve previously been told “how” to do computational social science, McLevey expertly ensures we understand “why” too.
Nice introductory text on computational methods for social scientists using Python. The text is rather comprehensive and covers a lot of contemporary problems which may be of great interest for aspirant scientists/ practitioners in their daily work.
The McLevey book covers modern machine learning style research for both information science and computing students. For other social science students who have programming skills, or are at a graduate level, then this book might also be a good resource with plenty of useful information. However it is written using a handbook style and lacking an academic thrust. It is very practical and exercise based. Students would still need the Oates book to help them writeup.