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Algorithm Audit: Why, What, and How?
Seeking to increasing the social awareness of citizens, institutions, and corporations with regard to the risks presented by the acritical use of algorithms in decision-making, this book explains the rationale and the methods of algorithm audit. Interdisciplinary in approach, it provides a systematic overview of the subject, supplying readers with clear definitions and practical tools for the audit of algorithms, while also taking account of the political, business, and vocational obstacles to the development of this new field. As such, it constitutes an essential resource for students and researchers across the social sciences and humanities, as well as for professionals and policymakers, with concerns about the social consequences of algorithmic decision-making.
Data Science and Social Research
This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and ...
What People Leave Behind
This open access book focuses on a particular but significant topic in the social sciences: the concepts of “footprint” and “trace”. It associates these concepts with hotly debated topics such as surveillance capitalism and knowledge society. The editors and authors discuss the concept footprints and traces as unintended by-products of other (differently focused and oriented) actions that remain empirically imprinted in virtual and real spaces. The volume therefore opens new scenarios for social theory and applied social research in asking what the stakes, risks and potential of this approach are. It systematically raises and addresses these questions within a consistent framework, b...
Data Science and Social Research II
The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences. The data revolution in social science research has not only produced new business models, but has also provided policymakers with better decision-making support tools. In this volume, statisticians, computer scientists and experts on social research discuss the opportunities and challenges of the social data revolution in order to pave the way for addressing new research problems. The respective contributions focus on complex social systems and current methodological advances in extracting social knowledge from large data sets, as well as modern social research on human behavior and society using large data sets. Moreover, they analyze integrated systems designed to take advantage of new social data sources, and discuss quality-related issues. The papers were originally presented at the 2nd International Conference on Data Science and Social Research, held in Milan, Italy, on February 4-5, 2019.
Heritage and Nationalism
How was the Roman Empire invoked in Brexit Britain and in Donald Trump’s United States of America, and to what purpose? And why is it critical to answer these kinds of questions? Heritage and Nationalism explores how people’s perceptions and experiences of the ancient past shape political identities in the digital age. It particularly examines the multiple ways in which politicians, parties and private citizens mobilise aspects of the Iron Age, Roman and Medieval past of Britain and Europe to include or exclude ‘others’ based on culture, religion, class, race, ethnicity, etc. Chiara Bonacchi draws on the results of an extensive programme of research involving both data-intensive and ...
Transformations in Social Science Research Methods during the COVID-19 Pandemic
This volume explores how researchers made innovative use of online technologies to innovate, define, and transform research methodologies in light of the varying impacts of the COVID-19 pandemic, especially those related to the ability to conduct qualitative research. The onset of the COVID-19 pandemic resulted in a radical shift in the way that people all over the world were/have been able to live, work, study, and conduct their daily lives. Academics and other professionals who routinely engage in research were no exception. The sudden, continued, and uneven need for health mandates calling for physical distancing added a particular layer of complexity for those who used research methods t...
Handbook of Research on Advanced Research Methodologies for a Digital Society
Doing research is an ever-changing challenge for social scientists. This challenge is harder than ever today as current societies are changing quickly and in many, sometimes conflicting, directions. Social phenomena, personal interactions, and formal and informal relationships are becoming more borderless and disconnected from the anchors of the offline “reality.” These dynamics are heavily marking our time and are suggesting evolutionary challenges in the ways we know, interpret, and analyze the world. Internet and computer-mediated communication (CMC) is being incorporated into every aspect of daily life, and social life has been deeply penetrated by the internet. This is due to recent...
Data Science Concepts and Techniques with Applications
This book comprehensively covers the topic of data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics. Followed by discussion on wide range of applications of data science and widely used techniques in data science. The second s...
Algorithm Audit: Why, What and How?
Seeking to increasing the social awareness of citizens, institutions, and corporations with regard to the risks presented by the acritical use of algorithms in decision-making, this book explains the rationale and the methods of algorithm audit. Interdisciplinary in approach, it provides a systematic overview of the subject, supplying readers with clear definitions and practical tools for the audit of algorithms, while also taking account of the political, business, and vocational obstacles to the development of this new field. As such, it constitutes an essential resource for students and researchers across the social sciences and humanities, as well as for professionals and policymakers, with concerns about the social consequences of algorithmic decision-making.
