From Social Science to Data Science : Key Data Collection and Analysis Skills in Python

From Social Science to Data Science : Key Data Collection and Analysis Skills in Python
ISBN: 9781529707489
Publication Date: 21 December 2022

From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding into computational techniques and seeing the bigger picture.

With key features such as tables, figures, step-by-step instruction and explanations giving a wider context, Hogan presents a clear and concise analysis on key data collection and skills in Python.

About the Author

Bernie Hogan (he/him/*) is a Senior Research Fellow at the Oxford Internet Institute and the current Director of the University of Oxford's MSc program in Social Data Science. Bernie's work specialises in how to leverage computational tools for creative, challenging, and engaging methodologies to address social science research questions about identity, sexuality, and community. His favourite work in this area focuses on the capture and analysis of personal social networks, using both pen-and-paper tools and the recent free opensource application Network Canvas. He also has a keen interest in how language is used to either bring people together or push them apart using large scale quantitative data. He has published over 40 peer reviewed articles and presented at over a hundred conferences, including several keynotes. His most famous work reconsidered Goffman's offline stage play metaphor of self-presentation for online life (Hogan, 2010).

This piece probably helped in popularising the term "algorithmic curation". Before working at the University of Oxford's Oxford Internet Institute he completed his undergraduate and graduate degrees in Canada. His undergraduate was in S...