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

Author:   Bernie Hogan
Publisher:   Sage Publications Ltd
ISBN:  

9781529707496


Pages:   400
Publication Date:   21 December 2022
Format:   Hardback
Availability:   To order   Availability explained
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From Social Science to Data Science: Key Data Collection and Analysis Skills in Python


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Full Product Details

Author:   Bernie Hogan
Publisher:   Sage Publications Ltd
Imprint:   Sage Publications Ltd
Weight:   0.930kg
ISBN:  

9781529707496


ISBN 10:   1529707498
Pages:   400
Publication Date:   21 December 2022
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Active
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

Table of Contents

Part I: Thinking Pragmatically Chapter 1. Introduction Chapter 2. The Series Chapter 3. The DataFrame Part II: Accessing and Converting Data Chapter 4. File Types Chapter 5. Merging and Grouping Data Chapter 6. Accessing the Web Chapter 7. Accessing APIs Part III. Interpreting Data: Expectations versus Observations Chapter 8. Research Questions Chapter 9. Visualising Expectations Part IV: Social Data Science in Practice: Four Approaches Chapter 10. Cleaning Data Chapter 11. Introducing Natural Language Processing Chapter 12. Introducing Time Series Data Chapter 13. Introducing Network Analysis Chapter 14. Introducing Geographic Information Systems Chapter 15. Conclusion About the Author

Reviews

Excellent. The students will love I think. It reminds me a bit of a Andy Field's SPSS/R books, which the students have also loved in the past too. This one has that flavour but also pushes the analytics into the contemporary era with Python. I expect it will be a real success. -- Emma Uprichard


Author Information

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 (https://www.networkcanvas.com). 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 (https://www.oii.ox.ac.uk) he completed his undergraduate and graduate degrees in Canada. His undergraduate was in Sociology and Computer Science at Memorial University in St. John’s, Newfoundland, Canada. His graduate work was in Sociology and Knowledge Media Design at the University of Toronto. During that time Bernie interned at Microsoft Research. Bernie lives in Oxford, UK with his husband and their sprawling vinyl record collection. He tweets (and collects vinyl) under the moniker “blurky” because it is a very rare word that sounds like Bernie. Most of this research is available from his departmental homepage, (https://www.oii.ox.ac.uk/people/hogan) and or/his GitHub, (https://www.github.com/berniehogan).

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