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: 6280

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: 3319954652

Category: Computers

Page: 388

View: 2661

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: 5723

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: 9160

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.

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: 5413

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.

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: 3505

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.

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: 5897

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.

Visualize This!

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Author: Nathan Yau

Publisher: John Wiley & Sons

ISBN: 3527760229

Category: Statistics / Graphic methods / Data processing

Page: 422

View: 5965

A guide on how to visualise and tell stories with data, providing practical design tips complemented with step-by-step tutorials.

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: 346

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

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: 9285

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.

Factfulness

Wie wir lernen, die Welt so zu sehen, wie sie wirklich ist

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Author: Hans Rosling,Anna Rosling Rönnlund,Ola Rosling

Publisher: Ullstein Buchverlage

ISBN: 3843717451

Category: Science

Page: 350

View: 9326

Es wird alles immer schlimmer, eine schreckliche Nachricht jagt die andere: Die Reichen werden reicher, die Armen ärmer. Es gibt immer mehr Kriege, Gewaltverbrechen, Naturkatastrophen. Viele Menschen tragen solche beängstigenden Bilder im Kopf. Doch sie liegen damit grundfalsch. Unser Gehirn verführt uns zu einer dramatisierenden Weltsicht, die mitnichten der Realität entspricht, wie der geniale Statistiker und Wissenschaftler Hans Rosling erklärt. Wer das Buch gelesen hat, wird • ein sicheres, auf Fakten basierendes Gerüst besitzen, um die Welt so zu sehen, wie sie wirklich ist • die zehn gängigsten Arten von aufgebauschten Geschichten erkennen • bessere Entscheidungen treffen können • wahre Factfulness erreichen – jene offene, neugierige und entspannte Geisteshaltung, in der Sie nur noch Ansichten teilen und Urteile fällen, die auf soliden Fakten basieren

Privacy, Big Data, and the Public Good

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Author: Julia Lane,Victoria Stodden,Stefan Bender,Helen Nissenbaum

Publisher: Cambridge University Press

ISBN: 1107067359

Category: Computers

Page: 344

View: 5525

Data access is essential for serving the public good. This book provides new frameworks to address the resultant privacy issues.

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: 1618

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.

Consumer Data Research

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Author: Paul Longley,James Cheshire,Alexander Singleton

Publisher: UCL Press

ISBN: 1787353885

Category: Social Science

Page: 198

View: 8586

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies. Praise for Consumer Data Research 'An insightful, state-of-the-art guide into the social and commercial value of applying geographical thinking to the study of consumer data.' Professor Richard Harris, University of Bristol 'An excellent guide to leveraging the value of academic research on valid data. Partnerships based around consumer data should be encouraged and supported by all and their outputs used to better the way we manage the world we live in.' Bill Grimsey, retailer and author of The Vanishing Highstreet 'The use of data from everyday consumer transactions is a potential game-changer for understanding economic and social patterns and trends. This is an excellent overview of the field.' Dr.Tom Smith, Managing Director, Office for National Statistics Data Science Campus

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: 4433

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.

Datenanalyse mit Python

Auswertung von Daten mit Pandas, NumPy und IPython

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Author: Wes McKinney

Publisher: O'Reilly

ISBN: 3960102143

Category: Computers

Page: 542

View: 2723

Erfahren Sie alles über das Manipulieren, Bereinigen, Verarbeiten und Aufbereiten von Datensätzen mit Python: Aktualisiert auf Python 3.6, zeigt Ihnen dieses konsequent praxisbezogene Buch anhand konkreter Fallbeispiele, wie Sie eine Vielzahl von typischen Datenanalyse-Problemen effektiv lösen. Gleichzeitig lernen Sie die neuesten Versionen von pandas, NumPy, IPython und Jupyter kennen.Geschrieben von Wes McKinney, dem Begründer des pandas-Projekts, bietet Datenanalyse mit Python einen praktischen Einstieg in die Data-Science-Tools von Python. Das Buch eignet sich sowohl für Datenanalysten, für die Python Neuland ist, als auch für Python-Programmierer, die sich in Data Science und Scientific Computing einarbeiten wollen. Daten und zugehöriges Material des Buchs sind auf GitHub verfügbar.Aus dem Inhalt:Nutzen Sie die IPython-Shell und Jupyter Notebook für das explorative ComputingLernen Sie Grundfunktionen und fortgeschrittene Features von NumPy kennenSetzen Sie die Datenanalyse-Tools der pandasBibliothek einVerwenden Sie flexible Werkzeuge zum Laden, Bereinigen, Transformieren, Zusammenführen und Umformen von DatenErstellen Sie interformative Visualisierungen mit matplotlibWenden Sie die GroupBy-Mechanismen von pandas an, um Datensätzen zurechtzuschneiden, umzugestalten und zusammenzufassenAnalysieren und manipulieren Sie verschiedenste Zeitreihen-DatenFür diese aktualisierte 2. Auflage wurde der gesamte Code an Python 3.6 und die neuesten Versionen der pandas-Bibliothek angepasst. Neu in dieser Auflage: Informationen zu fortgeschrittenen pandas-Tools sowie eine kurze Einführung in statsmodels und scikit-learn.

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: 6550

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.