John McLevey – författare

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 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. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed.

For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

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 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. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed.

For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

This new edition of The Sage Handbook of Social Network Analysis builds on the success of its predecessor, offering a comprehensive overview of social network analysis produced by leading international scholars in the field.

Brand new chapters provide both significant updates to topics covered in the first edition, as well as discussing cutting edge topics that have developed since, including new chapters on:

·       General issues such as social categories and computational social science;

·       Applications in contexts such as environmental policy, gender, ethnicity, cognition and social media and digital networks;

·       Concepts and methods such as centrality, blockmodeling, multilevel network analysis, spatial analysis, data collection, and beyond.

By providing authoritative accounts of the history, theories and methodology of various disciplines and topics, the second edition of The SAGE Handbook of Social Network Analysis is designed to provide a state-of-the-art presentation of classic and contemporary views, and to lay the foundations for the further development of the area.

PART 1: GENERAL ISSUES

PART 2: APPLICATIONS

PART 3: CONCEPTS AND METHODS

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 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. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed.

For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

This new edition of The Sage Handbook of Social Network Analysis builds on the success of its predecessor, offering a comprehensive overview of social network analysis produced by leading international scholars in the field.

Brand new chapters provide both significant updates to topics covered in the first edition, as well as discussing cutting edge topics that have developed since, including new chapters on:

·       General issues such as social categories and computational social science;

·       Applications in contexts such as environmental policy, gender, ethnicity, cognition and social media and digital networks;

·       Concepts and methods such as centrality, blockmodeling, multilevel network analysis, spatial analysis, data collection, and beyond.

By providing authoritative accounts of the history, theories and methodology of various disciplines and topics, the second edition of The SAGE Handbook of Social Network Analysis is designed to provide a state-of-the-art presentation of classic and contemporary views, and to lay the foundations for the further development of the area.

PART 1: GENERAL ISSUES

PART 2: APPLICATIONS

PART 3: CONCEPTS AND METHODS

This book examines the “oil-tourism interface”, the broad range of direct and indirect contact points between offshore oil extraction and nature-based tourism. Offshore oil extraction and nature-based tourism are pursued as development paths across the North Atlantic region. Offshore oil promises economic benefits from employment and royalty payments to host societies, but is based on fossil fuel-intensive resource extraction. Nature-based tourism, instead, is based on experiencing natural environments and encountering wildlife, including whales, seals, or seabirds. They share social-ecological space, such as oceans, coastlines, cities and towns where tourism and offshore oil operations and offices are located. However, they rarely share cultural or political space, in terms of media coverage, public debate, or policy discussion that integrates both modes of development. Through a comparative analysis of Denmark, Iceland, Newfoundland and Labrador, Norway, and Scotland, this book offers important lessons for how coastal societies can better navigate relationships between resource extraction and nature-based tourism in the interests of social-ecological wellbeing.

This book examines the “oil-tourism interface”, the broad range of direct and indirect contact points between offshore oil extraction and nature-based tourism. Offshore oil extraction and nature-based tourism are pursued as development paths across the North Atlantic region. Offshore oil promises economic benefits from employment and royalty payments to host societies, but is based on fossil fuel-intensive resource extraction. Nature-based tourism, instead, is based on experiencing natural environments and encountering wildlife, including whales, seals, or seabirds. They share social-ecological space, such as oceans, coastlines, cities and towns where tourism and offshore oil operations and offices are located. However, they rarely share cultural or political space, in terms of media coverage, public debate, or policy discussion that integrates both modes of development. Through a comparative analysis of Denmark, Iceland, Newfoundland and Labrador, Norway, and Scotland, this book offers important lessons for how coastal societies can better navigate relationships between resource extraction and nature-based tourism in the interests of social-ecological wellbeing.