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Reality mining : using big data to engineer a better world / by Nathan Eagle and Kate Greene.

By: Eagle, Nathan [author.].
Contributor(s): Greene, Kate, 1979- [author.].
Material type: TextTextSeries: JSTOR eBooks.Publisher: Cambridge, Massachusetts : The MIT Press, [2014]Copyright date: ©2014Description: 1 online resource (vi, 199 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9780262324564; 0262324563; 9780262324571; 0262324571.Subject(s): Data mining | Big data | Computer networks -- Social aspects | Information science -- Social aspects | Information science -- Statistical methodsAdditional physical formats: Print version:: Reality miningDDC classification: 006.3/12 LOC classification: QA76.9.D343 | E24 2014Online resources: Click here to view this ebook.
Partial contents:
I. The individual (one person) -- II. The neighborhood and the organization (10 to 1,000 people) -- III. The city (1,000 to 1,000,000 people) -- IV. The nation (1 millions to 100 million people) -- V. Reality mining the world's data (100 million to 7 billion people)
Summary: In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- Edited summary from book.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
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QA76.9.D343 E24 2014 (Browse shelf) https://ezproxy.uttyler.edu/login?url=http://www.jstor.org/stable/10.2307/j.ctt9qf8q3 Available ocn886539978

Includes bibliographical references and index.

I. The individual (one person) -- II. The neighborhood and the organization (10 to 1,000 people) -- III. The city (1,000 to 1,000,000 people) -- IV. The nation (1 millions to 100 million people) -- V. Reality mining the world's data (100 million to 7 billion people)

Print version record.

In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- Edited summary from book.

Reviews provided by Syndetics

CHOICE Review

Eagle (CEO, Jana; adjunct, Harvard and Northeastern) and Greene (freelance journalist) believe that engineers with access to big data can make the world a better place. Although Eagle has authored dozens of academic papers over the past decade, in this book, the authors explicitly choose to focus on corporate projects rather than academic work. The result is a volume that is as dehumanizing as the term social engineering and as lacking in rigor as a trade magazine. Much of the information provided is anecdotal or conjectural: "company X is doing Y, which might solve problem Z." Privacy concerns can cause public relations problems, but those might be overcome by providing incentives. The book is organized around four granularity levels: individual, community, national, and global. However, the presentation repeats common material across all four levels, such as the use of call data records and certain corporate projects. People not already familiar with the extent of their "digital exhaust" may find the book enlightening, as might people who do not know that disparate data sets can be combined to uncover hidden relationships. But readers looking to understand the dark side of big data (its use by marketers, criminals, and malevolent governments) will find few insights here. Summing Up: Optional. General readers. --Christopher Vickery, Queens College of CUNY

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