Data and Society PDF Download

Author: Anne Beaulieu
Publisher: SAGE
ISBN: 1529765129
Category : Social Science
Languages : en
Pages : 225

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Book Description
Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.

Author: Evans, Jeff
Publisher: Policy Press
ISBN: 1447348214
Category : Social Science
Languages : en
Pages : 414

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Book Description
Statistical data and evidence-based claims are increasingly central to our everyday lives. Critically examining ‘Big Data’, this book charts the recent explosion in sources of data, including those precipitated by global developments and technological change. It sets out changes and controversies related to data harvesting and construction, dissemination and data analytics by a range of private, governmental and social organisations in multiple settings. Analysing the power of data to shape political debate, the presentation of ideas to us by the media, and issues surrounding data ownership and access, the authors suggest how data can be used to uncover injustices and to advance social progress.

Author: Martin Engebretsen
Publisher: Amsterdam University Press
ISBN: 9463722904
Category : Computers
Languages : en
Pages : 466

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Book Description
Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

Author: Yanni Alexander Loukissas
Publisher: MIT Press
ISBN: 0262039664
Category : Computers
Languages : en
Pages : 267

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Book Description
How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.

Author: Mirko Tobias Schäfer
Publisher:
ISBN: 9789462981362
Category : Big data
Languages : en
Pages : 267

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Book Description
The ability to gather data that can be crunched by machines is valuable for studying society. The new methods needed to work it require new skills and new ways of thinking about best research practices. This book reflects on the role and usefulness of big data, challenging overly optimistic expectations about what it can reveal, introducing practices and methods for its analysis and visualization, and raising important political and ethical questions regarding its collection, handling, and presentation.

Author: Catherine Knight Steele
Publisher: NYU Press
ISBN: 1479808385
Category : Social Science
Languages : en
Pages : 208

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Book Description
"This book traces the long arc of Black women's relationship with technology from the antebellum south to the social media era demonstrating how digital culture transforms and is transformed by Black feminist thought"--

Author: Catherine D'Ignazio
Publisher: MIT Press
ISBN: 0262358530
Category : Social Science
Languages : en
Pages : 328

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Book Description
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

Author: Sandra Gonzalez-Bailon
Publisher: MIT Press
ISBN: 0262343460
Category : Social Science
Languages : en
Pages : 257

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Book Description
How data science and the analysis of networks help us solve the puzzle of unintended consequences. Social life is full of paradoxes. Our intentional actions often trigger outcomes that we did not intend or even envision. How do we explain those unintended effects and what can we do to regulate them? In Decoding the Social World, Sandra González-Bailón explains how data science and digital traces help us solve the puzzle of unintended consequences—offering the solution to a social paradox that has intrigued thinkers for centuries. Communication has always been the force that makes a collection of people more than the sum of individuals, but only now can we explain why: digital technologies have made it possible to parse the information we generate by being social in new, imaginative ways. And yet we must look at that data, González-Bailón argues, through the lens of theories that capture the nature of social life. The technologies we use, in the end, are also a manifestation of the social world we inhabit. González-Bailón discusses how the unpredictability of social life relates to communication networks, social influence, and the unintended effects that derive from individual decisions. She describes how communication generates social dynamics in aggregate (leading to episodes of “collective effervescence”) and discusses the mechanisms that underlie large-scale diffusion, when information and behavior spread “like wildfire.” She applies the theory of networks to illuminate why collective outcomes can differ drastically even when they arise from the same individual actions. By opening the black box of unintended effects, González-Bailón identifies strategies for social intervention and discusses the policy implications—and how data science and evidence-based research embolden critical thinking in a world that is constantly changing.

Author: Anna Leon-Guerrero
Publisher: SAGE Publications
ISBN: 1506390811
Category : Social Science
Languages : en
Pages : 645

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Book Description
The authors are proud sponsors of the 2020 SAGE Keith Roberts Teaching Innovations Award—enabling graduate students and early career faculty to attend the annual ASA pre-conference teaching and learning workshop. Essentials of Social Statistics for a Diverse Society, Third Edition, is a more streamlined, less expensive version of the successful Social Statistics for a Diverse Society. As in the parent text, the Essentials version does more than introduce students to the statistical techniques used by social scientists. It is distinct for the use of real data from contemporary social issues, illustrating the interplay between social concerns and methods of inquiry, and for a strong emphasis on race, class, gender, and other statuses to show how statistics can be a tool for understanding the richness of social differences within society. With a wide range of examples and exercises taken from current events and published research, frequent illustrations, and a focus on student learning, this book continues to be an accessible and engaging resource for students. "I think this textbook is incredibly readable. It presents statistics in a manner that is easy to grasp and comprehend but is still rigorous in terms of the content covered." —Amy Lucas, University of Houston–Clear Lake A Complete Teaching & Learning Package SAGE edge FREE online resources for students that make learning easier. See how your students benefit.

Author: Frank Pasquale
Publisher: Harvard University Press
ISBN: 0674967100
Category : Law
Languages : en
Pages : 320

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Book Description
Every day, corporations are connecting the dots about our personal behavior—silently scrutinizing clues left behind by our work habits and Internet use. The data compiled and portraits created are incredibly detailed, to the point of being invasive. But who connects the dots about what firms are doing with this information? The Black Box Society argues that we all need to be able to do so—and to set limits on how big data affects our lives. Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy. Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical. But leaks, whistleblowers, and legal disputes have shed new light on automated judgment. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior. Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others.