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Author: Juyoung Song Publisher: Cambridge Scholars Publishing ISBN: 1527536793 Category : Social Science Languages : en Pages : 311
Book Description
This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts useful information from online documents; opinion mining, which analyses the emotions contained in documents; machine learning for crime prediction; and visualization analysis. To accurately predict crimes using machine learning, it is necessary to procure high-quality training data. Machine learning combined with high-quality data can be used to develop excellent crime-prediction artificial intelligences. As such, the book will serve to be a practical guide to anyone wishing to predict rapidly-changing social phenomena and draw creative conclusions using big-data analysis.
Author: Juyoung Song Publisher: Cambridge Scholars Publishing ISBN: 1527536793 Category : Social Science Languages : en Pages : 311
Book Description
This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts useful information from online documents; opinion mining, which analyses the emotions contained in documents; machine learning for crime prediction; and visualization analysis. To accurately predict crimes using machine learning, it is necessary to procure high-quality training data. Machine learning combined with high-quality data can be used to develop excellent crime-prediction artificial intelligences. As such, the book will serve to be a practical guide to anyone wishing to predict rapidly-changing social phenomena and draw creative conclusions using big-data analysis.
Author: Ian Foster Publisher: CRC Press ISBN: 1000208591 Category : Mathematics Languages : en Pages : 413
Book Description
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
Author: Gian Maria Campedelli Publisher: Routledge ISBN: 1000596583 Category : Computers Languages : en Pages : 208
Book Description
Machine Learning for Criminology and Crime Research: At the Crossroads reviews the roots of the intersection between machine learning, artificial intelligence (AI), and research on crime; examines the current state of the art in this area of scholarly inquiry; and discusses future perspectives that may emerge from this relationship. As machine learning and AI approaches become increasingly pervasive, it is critical for criminology and crime research to reflect on the ways in which these paradigms could reshape the study of crime. In response, this book seeks to stimulate this discussion. The opening part is framed through a historical lens, with the first chapter dedicated to the origins of the relationship between AI and research on crime, refuting the "novelty narrative" that often surrounds this debate. The second presents a compact overview of the history of AI, further providing a nontechnical primer on machine learning. The following chapter reviews some of the most important trends in computational criminology and quantitatively characterizing publication patterns at the intersection of AI and criminology, through a network science approach. This book also looks to the future, proposing two goals and four pathways to increase the positive societal impact of algorithmic systems in research on crime. The sixth chapter provides a survey of the methods emerging from the integration of machine learning and causal inference, showcasing their promise for answering a range of critical questions. With its transdisciplinary approach, Machine Learning for Criminology and Crime Research is important reading for scholars and students in criminology, criminal justice, sociology, and economics, as well as AI, data sciences and statistics, and computer science.
Author: Euroscicon Publisher: EuroScicon ISBN: Category : Computers Languages : en Pages : 43
Book Description
March 04-05, 2019, Barcelona, Spain Key Topics: Big Data Analytics ,Big Data Algorithms ,Big Data In Bioinformatics ,Data Mining With Big Data ,Visualization In Big Data ,Big Data In Neural Network For Deep Learning ,High Performance Computing For Big Data ,Machine Learning In Data Science ,Open Science In Big Data ,Hadoop Map-Reduce For Analyzing Information ,Regression In Data Science ,Big Data Applications
Author: Paul Attewell Publisher: Univ of California Press ISBN: 0520280970 Category : Social Science Languages : en Pages : 264
Book Description
"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.
Author: Mathieu Deflem Publisher: Emerald Group Publishing ISBN: 1787698653 Category : Social Science Languages : en Pages : 216
Book Description
As scholarly work on crime, deviance, criminal justice, and social control advances and sophisticated methods of investigation develop, chapter authors demonstrate the methodological maturity and diversity of current empirical research in criminology and criminal justice.
Author: Eugene McLaughlin Publisher: SAGE ISBN: 1526480352 Category : Social Science Languages : en Pages : 1188
Book Description
Now in its fourth edition, The SAGE Dictionary of Criminology has established itself as an authoritative reference text for the key concepts, theories, and methods in criminology and criminal justice. Edited by two leading figures in the field of criminology, the book includes over 325 entries from 120 academics and practitioners from Europe, USA, Canada, China, Australia and New Zealand. All concepts are precisely defined, followed by a section outlining the concept’s origins, development and general significance, a list of associated concepts, and finally, further reading suggestions to help extend students′ knowledge. New to the 4th Edition: Up to 30 new entries, covering topics such as cyber security, wildlife crime, crimmigration, and penal populism. Updates to entries including new ‘further reading’ suggestions A new section ′Evaluation′ is included for concepts considered to have the greatest theoretical weight, allowing for a critical assessment of how the concept can be debated, challenged and reworked. Further contributions from international academics. An essential reference tool for students and academics within criminology, criminal justice and legal studies.
Author: Faye S. Taxman Publisher: Routledge ISBN: 1317402820 Category : Social Science Languages : en Pages : 650
Book Description
The Handbook on Risk and Need Assessment: Theory and Practice covers risk assessments for individuals being considered for parole or probation. Evidence-based approaches to such decisions help take the emotion and politics out of community corrections. As the United States begins to back away from ineffective, expensive policies of mass incarceration, this handbook will provide the resources needed to help ensure both public safety and the effective rehabilitation of offenders. The ASC Division on Corrections & Sentencing Handbook Series will publish volumes on topics ranging from violence risk assessment to specialty courts for drug users, veterans, or the mentally ill. Each thematic volume focuses on a single topical issue that intersects with corrections and sentencing research.
Author: Anita Lavorgna Publisher: Springer Nature ISBN: 3030748375 Category : Social Science Languages : en Pages : 548
Book Description
This edited book promotes and facilitates cybercrime research by providing a cutting-edge collection of perspectives on the critical usage of online data across platforms, as well as the implementation of both traditional and innovative analysis methods. The accessibility, variety and wealth of data available online presents substantial opportunities for researchers from different disciplines to study cybercrimes and, more generally, human behavior in cyberspace. The unique and dynamic characteristics of cyberspace often demand cross-disciplinary and cross-national research endeavors, but disciplinary, cultural and legal differences can hinder the ability of researchers to collaborate. This work also provides a review of the ethics associated with the use of online data sources across the globe. The authors are drawn from multiple disciplines and nations, providing unique insights into the value and challenges evident in online data use for cybercrime scholarship. It is a key text for researchers at the upper undergraduate level and above.
Author: Juyoung Song
Author: Juyoung Song
Author: Ian Foster
Author: Gian Maria Campedelli
Author: Euroscicon
Author: Paul Attewell
Author: Mathieu Deflem
Author: Eugene McLaughlin
Author: Faye S. Taxman
Author: Anita Lavorgna
Author: Taylor & Francis Group