Big Data and Social Science

A Practical Guide to Methods and Tools

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Author: Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane

Publisher: CRC Press

ISBN: 1498751431

Category: Mathematics

Page: 376

View: 8985

Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.

Big Data in Computational Social Science and Humanities

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Author: Shu-Heng Chen

Publisher: Springer

ISBN: 9783319954646

Category: Computers

Page: 407

View: 9932

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.

Data Science and Social Research

Epistemology, Methods, Technology and Applications

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Author: N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino

Publisher: Springer

ISBN: 3319554778

Category: Social Science

Page: 300

View: 6243

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 decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.

Big Data, Crime and Social Control

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Author: Aleš Završnik

Publisher: Routledge

ISBN: 1315395762

Category: Social Science

Page: 230

View: 5381

From predictive policing to self-surveillance to private security, the potential uses to of big data in crime control pose serious legal and ethical challenges relating to privacy, discrimination, and the presumption of innocence. The book is about the impacts of the use of big data analytics on social and crime control and on fundamental liberties. Drawing on research from Europe and the US, this book identifies the various ways in which law and ethics intersect with the application of big data in social and crime control, considers potential challenges to human rights and democracy and recommends regulatory solutions and best practice. This book focuses on changes in knowledge production and the manifold sites of contemporary surveillance, ranging from self-surveillance to corporate and state surveillance. It tackles the implications of big data and predictive algorithmic analytics for social justice, social equality, and social power: concepts at the very core of crime and social control. This book will be of interest to scholars and students of criminology, sociology, politics and socio-legal studies.

Psychologische Methodenlehre

eine orientierende Einführung

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Author: Heinrich Wottawa

Publisher: Beltz Juventa

ISBN: 9783779903147

Category: Psychologie

Page: 235

View: 5044

Big Data in Complex and Social Networks

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Author: My T. Thai,Weili Wu,Hui Xiong

Publisher: CRC Press

ISBN: 1315396696

Category: Business & Economics

Page: 252

View: 1395

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

Thinking Big Data in Geography

New Regimes, New Research

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Author: Jim Thatcher

Publisher: U of Nebraska Press

ISBN: 1496205359

Category: SCIENCE

Page: 318

View: 5018

Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob Kitchin, Renee Sieber, and Mark Graham. Part 1 explores how the advent of geoweb technologies and big data sets has influenced some of geography's major subdisciplines: urban politics and political economy, human-environment interactions, and geographic information sciences. Part 2 addresses how the geographic study of big data has implications for other disciplinary fields, notably the digital humanities and the study of social justice. The volume concludes with theoretical applications of the geoweb and big data as they pertain to society as a whole, examining the ways in which user-generated data come into the world and are complicit in its unfolding. The contributors raise caution regarding the use of spatial big data, citing issues of accuracy, surveillance, and privacy.

Big Data and Analytics for Infectious Disease Research, Operations, and Policy

Proceedings of a Workshop

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Author: National Academies of Sciences, Engineering, and Medicine,Health and Medicine Division,Board on Global Health,Forum on Microbial Threats

Publisher: National Academies Press

ISBN: 030945011X

Category: Medical

Page: 98

View: 6278

With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.

Computational Social Science

Discovery and Prediction

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Author: R. Michael Alvarez

Publisher: Cambridge University Press

ISBN: 1316531287

Category: Political Science

Page: N.A

View: 5824

Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.

Computational Social Science in the Age of Big Data

Concepts, Methodologies, Tools, and Applications

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Author: Martin Welker,Cathleen M. Stützer,Marc Egger

Publisher: Herbert von Halem Verlag

ISBN: 3869622687

Category: Business & Economics

Page: 460

View: 2533

Der Sammelband Computational Social Science in the Age of Big Data beschäftigt sich mit Konzepten, Methoden, Tools und Anwendungen (automatisierter) datengetriebener Forschung mit sozialwissenschaftlichem Hintergrund. Der Fokus des Bandes liegt auf der Etablierung der Computational Social Science (CSS) als aufkommendes Forschungs- und Anwendungsfeld. Es werden Beiträge international namhafter Autoren präsentiert, die forschungs- und praxisrelevante Themen dieses Bereiches besprechen. Die Herausgeber forcieren dabei einen interdisziplinären Zugang zum Feld, der sowohl Online-Forschern aus der Wissenschaft wie auch aus der angewandten Marktforschung einen Einstieg bietet.

big data @ work

Chancen erkennen, Risiken verstehen

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Author: Thomas H. Davenport

Publisher: Vahlen

ISBN: 3800648156

Category: Fiction

Page: 214

View: 5541

Big Data in Unternehmen. Dieses neue Buch gibt Managern ein umfassendes Verständnis dafür, welche Bedeutung Big Data für Unternehmen zukünftig haben wird und wie Big Data tatsächlich genutzt werden kann. Am Ende jedes Kapitels aktivieren Fragen, selbst nach Lösungen für eine erfolgreiche Implementierung und Nutzung von Big Data im eigenen Unternehmen zu suchen. Die Schwerpunkte - Warum Big Data für Sie und Ihr Unternehmen wichtig ist - Wie Big Data Ihre Arbeit, Ihr Unternehmen und Ihre Branche verändern - - wird - Entwicklung einer Big Data-Strategie - Der menschliche Aspekt von Big Data - Technologien für Big Data - Wie Sie erfolgreich mit Big Data arbeiten - Was Sie von Start-ups und Online-Unternehmen lernen können - Was Sie von großen Unternehmen lernen können: Big Data und Analytics 3.0 Der Experte Thomas H. Davenport ist Professor für Informationstechnologie und -management am Babson College und Forschungswissenschaftler am MIT Center for Digital Business. Zudem ist er Mitbegründer und Forschungsdirektor am International Institute for Analytics und Senior Berater von Deloitte Analytics.

Big Data

Die Revolution, die unser Leben verändern wird

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Author: Viktor Mayer-Schönberger,Viktor; Cukier Mayer-Schönberger

Publisher: Redline Wirtschaft

ISBN: 3864144590

Category: Political Science

Page: 288

View: 7073

Ob Kaufverhalten, Grippewellen oder welche Farbe am ehesten verrät, ob ein Gebrauchtwagen in einem guten Zustand ist – noch nie gab es eine solche Menge an Daten und noch nie bot sich die Chance, durch Recherche und Kombination in der Daten¬flut blitzschnell Zusammenhänge zu entschlüsseln. Big Data bedeutet nichts weniger als eine Revolution für Gesellschaft, Wirtschaft und Politik. Es wird die Weise, wie wir über Gesundheit, Erziehung, Innovation und vieles mehr denken, völlig umkrempeln. Und Vorhersagen möglich machen, die bisher undenkbar waren. Die Experten Viktor Mayer-Schönberger und Kenneth Cukier beschreiben in ihrem Buch, was Big Data ist, welche Möglichkeiten sich eröffnen, vor welchen Umwälzungen wir alle stehen – und verschweigen auch die dunkle Seite wie das Ausspähen von persönlichen Daten und den drohenden Verlust der Privatsphäre nicht.

The SAGE Handbook of Social Media Research Methods

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Author: Luke Sloan,Anabel Quan-Haase

Publisher: SAGE

ISBN: 1473987970

Category: Social Science

Page: 728

View: 6321

The SAGE Handbook of Social Media Research Methods offers a step-by-step guide to overcoming the challenges inherent in research projects that deal with ‘big and broad data’, from the formulation of research questions through to the interpretation of findings. The handbook includes chapters on specific social media platforms such as Twitter, Sina Weibo and Instagram, as well as a series of critical chapters. The holistic approach is organised into the following sections: Conceptualising & Designing Social Media Research Collection & Storage Qualitative Approaches to Social Media Data Quantitative Approaches to Social Media Data Diverse Approaches to Social Media Data Analytical Tools Social Media Platforms This handbook is the single most comprehensive resource for any scholar or graduate student embarking on a social media project.

'Applied Big Data Analytics'

Evolution, Platforms & Tools, Use Cases, Benefits, Impact and Paradox'

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Author: Ajit Kumar Roy

Publisher: CreateSpace

ISBN: 9781516963140

Category:

Page: 368

View: 4106

The impact of data abundance extends well beyond business ensuring funding for social programs. Big Data has the potential to be "humanity's dashboard," an intelligent tool that can help combat poverty, crime and pollution. All these burning issues are covered in the following chapters of the book entitled, 'Applied Big Data Analytics: Evolution, Platforms & Tools, Use cases, Benefits, Impact and Paradox' 1History of Big Datahttps: //ssl.images-createspace.com/tsw/img/ajax/choosernav-right_off.gif 2Definitions & Surprising Statistics about Big Data 4Open Source Big Data Analytical Platforms and Tools 5Use Cases & Advantages & Benefits of Big Data 6Impact of Big Data on Business, Economy and Society 7Impact of Big data on Healthcare 8Transforming Social Welfare with Analytics 9The Future of Big Data & Risks, Challenges and Paradox A recent Accenture and GE study found that almost 90 percent of companies list Big Data analytics as one of their top priorities, and believe that Big Data analytics will shift the competitive landscape within the next three years. The book provides an opportunity for scholars and researchers in big data and health science, business intelligence, social scientists in developments to update their knowledge on the abovementioned issues. The chapters presented is based on an extensive research with the literature from across humanities, social sciences and the sciences and from popular culture, journalism, and industry publications, and based on my lifelong experience of working earlier in Analytics and now in Big Data Analytics as a Statistician.

Data Science and Simulation in Transportation Research

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Author: Janssens, Davy

Publisher: IGI Global

ISBN: 1466649216

Category: Computers

Page: 350

View: 9874

Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important challenge. Data Science and Simulation in Transportation Research highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society. Bringing together novel ideas grounded in big data from various data mining and transportation science sources, this book is an essential tool for professionals, students, and researchers in the fields of transportation research and data mining.

Politics and Big Data

Nowcasting and Forecasting Elections with Social Media

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Author: Andrea Ceron,Luigi Curini,Stefano Maria Iacus

Publisher: Routledge

ISBN: 1317134133

Category: Political Science

Page: 188

View: 1430

The importance of social media as a way to monitor an electoral campaign is well established. Day-by-day, hour-by-hour evaluation of the evolution of online ideas and opinion allows observers and scholars to monitor trends and momentum in public opinion well before traditional polls. However, there are difficulties in recording and analyzing often brief, unverified comments while the unequal age, gender, social and racial representation among social media users can produce inaccurate forecasts of final polls. Reviewing the different techniques employed using social media to nowcast and forecast elections, this book assesses its achievements and limitations while presenting a new technique of "sentiment analysis" to improve upon them. The authors carry out a meta-analysis of the existing literature to show the conditions under which social media-based electoral forecasts prove most accurate while new case studies from France, the United States and Italy demonstrate how much more accurate "sentiment analysis" can prove.

Psychoanalysis and Digital Culture

Audiences, Social Media, and Big Data

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Author: Jacob Johanssen

Publisher: Routledge

ISBN: 1351052047

Category: Social Science

Page: 206

View: 9985

Psychoanalysis and Digital Culture offers a comprehensive account of our contemporary media environment—digital culture and audiences in particular—by drawing on psychoanalysis and media studies frameworks. It provides an introduction to the psychoanalytic affect theories of Sigmund Freud and Didier Anzieu and applies them theoretically and methodologically in a number of case studies. Johanssen argues that digital media fundamentally shape our subjectivities on affective and unconscious levels, and he critically analyses phenomena such as television viewing, Twitter use, affective labour on social media, and data-mining. How does watching television involve the body? Why are we so drawn to reality television? Why do we share certain things on social media and not others? How are bodies represented on social media? How do big data and data mining influence our identities? Can algorithms help us make better decisions? These questions amongst others are addressed in the chapters of this wide-ranging book. Johanssen shows in a number of case studies how a psychoanalytic angle can bring new insights to audience studies and digital media research more generally. From audience research with viewers of the reality television show Embarrassing Bodies and how they unconsciously used it to work through feelings about their own bodies, to a critical engagement with Hardt and Negri's notion of affective labour and how individuals with bodily differences used social media for their own affective-digital labour, the book suggests that an understanding of affect based on Freud and Anzieu is helpful when thinking about media use. The monograph also discusses the perverse implications of algorithms, big data and data mining for subjectivities. In drawing on empirical data and examples throughout, Johanssen presents a compelling analysis of our contemporary media environment.

Ethical Reasoning in Big Data

An Exploratory Analysis

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Author: Jeff Collmann,Sorin Adam Matei

Publisher: Springer

ISBN: 3319284223

Category: Computers

Page: 192

View: 983

This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public’s trust in the abilities of particular scientists and scientific institutions constitutes one of this book’s major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest – sometimes implicitly – a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature.