Images as Data for Social Science Research PDF Download

Author: Nora Webb Williams
Publisher: Cambridge University Press
ISBN: 1108852181
Category : Political Science
Languages : en
Pages : 108

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Book Description
Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.

Author: Nora Webb Williams
Publisher: Cambridge University Press
ISBN: 9781108816854
Category : Political Science
Languages : en
Pages : 75

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Book Description
Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.

Author: Anol Bhattacherjee
Publisher: CreateSpace
ISBN: 9781475146127
Category : Science
Languages : en
Pages : 156

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Book Description
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Author: Gregory C. Stanczak
Publisher: SAGE Publications
ISBN: 1483389383
Category : Social Science
Languages : en
Pages : 650

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Book Description
Visual Research Methods: Image, Society, and Representation addresses the growing question in social research of how to critically incorporate visual data and visual methodologies in ways that expand and enhance the researcher′s repertoire for understanding and teaching about the social world. Editor Gregory C. Stanczak crisscrosses disciplines in ways that highlight the multiple manifestations of this newer interdisciplinary trend. Beyond methodological interests, the rich diversity of subject matter provides this volume′s pedagogical punch. Key Features Provides a valuable framework for classroom use and comparative analysis: Organized around three themes in visual research—methodology, epistemological reflection, and theoretical contribution of images Addresses a wide range of topics: Original and reprinted works by leading qualitative researchers from various fields, including Sociology, Education, Political Science, Religion, History, and Gender Studies Offers a roadmap to common issues and topics: Reader′s guide connects different chapters to different conceptual themes and methodological approaches Presents vivid visual data: Methodologies go beyond photography alone and include video and virtual research Intended Audience: This is an excellent text for advanced undergraduate and graduate courses in social research across disciplines such as Sociology, Education, Cultural Studies, Anthropology, American Studies, Communications, Gender Studies, and Political Science.Vi

Author: Perry, S. Marshall
Publisher: IGI Global
ISBN: 1522536175
Category : Social Science
Languages : en
Pages : 349

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Book Description
Making research in all fields of study readily available is imperative in order to circulate new information and upcoming trends. This is possible through the efficient utilization of collections of information. Maximizing Social Science Research Through Publicly Accessible Data Sets is an essential reference source for the latest academic perspectives on a wide range of methodologies and large data sets with the purpose of enhancing research in the areas of human society and social relationships. Featuring coverage on a broad range of topics such as student achievement, teacher efficacy, and instructional leadership, this book is ideally designed for academicians, researchers, and practitioners seeking material on the availability and distribution methods of research content.

Author: Ian Foster
Publisher: CRC Press
ISBN: 1498751431
Category : Mathematics
Languages : en
Pages : 493

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Book Description
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.

Author: Johannes Wheeldon
Publisher: SAGE
ISBN: 145223955X
Category : Social Science
Languages : en
Pages : 225

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Book Description
This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, "see" analysis strategies, and assist in the development and writing of research reports.

Author: Rik Das
Publisher: CRC Press
ISBN: 1000280470
Category : Computers
Languages : en
Pages : 197

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Book Description
Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/

Author: N. Carlo Lauro
Publisher: Springer
ISBN: 3319554778
Category : Social Science
Languages : en
Pages : 292

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Book Description
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.

Author: Eszter Hargittai
Publisher: Columbia University Press
ISBN: 0231548001
Category : Social Science
Languages : en
Pages : 478

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Book Description
The era of digital communication provides endless opportunities for the collection and analysis of social data in novel ways. It also presents new and unanticipated challenges, as researchers are often inventing elements of their methodologies on the fly or studying a phenomenon or media platform for the first time. Research Exposed offers in-depth, behind-the-scenes accounts of doing empirical social science in this new paradigm. Through firsthand descriptions of innovative research projects, it shares lessons learned from over a dozen scholars’ cutting-edge work. These candid accounts describe what can go wrong when pioneering new genres of research and how such difficulties can be overcome, giving both big-picture reflection and actionable advice. The chapters discuss a variety of methods, ranging from the completely novel to the use of more traditional approaches in the digital context, and cover research questions relevant to a range of disciplines, including sociology, political science, communication, information studies, and anthropology. By focusing attention on the concrete details seldom discussed in final project write-ups or traditional research guides, Research Exposed helps equip junior and senior scholars alike with essential information that is all too often left with no outlet for sharing. It offers important insights into how empirical social science research can be both innovative and rigorous when dealing with the opportunities and challenges presented by digital media.