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Programming with Python for Social Scientists
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Programming with Python for Social Scientists

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December 2019 | 328 pages | SAGE Publications Ltd
As data become ‘big’, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of – and control over – how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including:
  • the fundamentals of why and how to do your own programming in social scientific research,
  • questions of ethics and research design,
  • a clear, easy to follow ‘how-to’ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more.

Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.

 

 
Introduction
 
Chapter 1. What is Programming? And What Could it Mean for Social Science Research?
 
Chapter 2. Programming-as-Social-Science (Critical Coding
 
Chapter 3. Setting Up to Start Coding
 
Chapter 4. Core Concepts/Objects
 
Chapter 5. Structuring Objects
 
Chapter 6. Building Better Code with (Slightly) More Complex Concepts/Objects
 
Chapter 7. Building New Objects with Classes
 
Chapter 8. Useful Extra Concepts/Practices
 
Chapter 9. Designing Research that Features Programming
 
Chapter 10. Working with Text Files
 
Chapter 11. Data Collection: Using Social Media APIs
 
Chapter 12. Data Decoding/Encoding in Popular Formats (CSV, JSON and XML)
 
Chapter 13. Data Collection: Web Scraping
 
Chapter 14. Visualising Data
 
Conclusion: Using Your Programming-as-Social-Science Mindset

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Great resource for all students and researchers looking for a clear, accessible, yet comprehensive introduction to Python and coding.

Nicola Perra
University of Greenwich

This is an engaging, insightful and sophisticated guide to Python for social scientists. It's a manual of the highest quality and a practice led intervention with the potential to shape the future of the digital social sciences. I can't recommend it highly enough. 

 

Mark Carrigan
University of Cambridge

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Phillip D. Brooker

Phillip Brooker is a Lecturer in Sociology at the University of Liverpool, with interdisciplinary research interests in and around ethnomethodology and conversation analysis, science and technology studies, computer-supported cooperative work, and human-computer interaction. On the platform of a record of research in the emerging field of digital methods and social media analytics (having contributed to the development of a Twitter data collection and visual analysis package called Chorus (www.chorusanalytics.co.uk)), Phillip's current research interests lie in exploring the potential for computer programming to feature in core social... More About Author

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