Download or read book Big Data Analysis Using Machine Learning for Social Scientists and Criminologists written by Juyoung Song and published by Cambridge Scholars Publishing. This book was released on 2019-07-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2020-11-17 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2016-09-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data written by Benoit Leclerc and published by Routledge. This book was released on 2020-02-14 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The internet has launched the world into an era into which enormous amounts of data are generated every day through technologies with both positive and negative consequences. This often refers to big data . This book explores big data in organisations operating in the criminology and criminal justice fields. Big data entails a major disruption in the ways we think about and do things, which certainly applies to most organisations including those operating in the criminology and criminal justice fields. Big data is currently disrupting processes in most organisations – how different organisations collaborate with one another, how organisations develop products or services, how organisations can identify, recruit, and evaluate talent, how organisations can make better decisions based on empirical evidence rather than intuition, and how organisations can quickly implement any transformation plan, to name a few. All these processes are important to tap into, but two underlying processes are critical to establish a foundation that will permit organisations to flourish and thrive in the era of big data – creating a culture more receptive to big data and implementing a systematic data analytics-driven process within the organisation. Written in a clear and direct style, this book will appeal to students and scholars in criminology, criminal justice, sociology, and cultural studies but also to government agencies, corporate and non-corporate organisations, or virtually any other institution impacted by big data.
Download or read book Data Mining for the Social Sciences written by Paul Attewell and published by Univ of California Press. This book was released on 2015-05 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Download or read book Big Data Science for Criminology and the Social Sciences written by Marcello Trovati and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "There is an increasing prevalence of large and complex datasets within the social sciences, and notably criminology in recent years. This data explosion has led to the development of specialized techniques for extracting information from such data. This book presents an introduction to "Big Data Science" for criminology and the social sciences, taking a case study-based approach to explaining the concepts. The theory is introduced as needed to answer scientific questions based on real data problems in the application areas. Some R and Python code is included to give support with implementation of the methods."--Provided by publisher.
Download or read book Machine Learning for Experiments in the Social Sciences written by Jon Green and published by Cambridge University Press. This book was released on 2023-04-13 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causal inference and machine learning are typically introduced in the social sciences separately as theoretically distinct methodological traditions. However, applications of machine learning in causal inference are increasingly prevalent. This Element provides theoretical and practical introductions to machine learning for social scientists interested in applying such methods to experimental data. We show how machine learning can be useful for conducting robust causal inference and provide a theoretical foundation researchers can use to understand and apply new methods in this rapidly developing field. We then demonstrate two specific methods – the prediction rule ensemble and the causal random forest – for characterizing treatment effect heterogeneity in survey experiments and testing the extent to which such heterogeneity is robust to out-of-sample prediction. We conclude by discussing limitations and tradeoffs of such methods, while directing readers to additional related methods available on the Comprehensive R Archive Network (CRAN).
Download or read book Machine Learning for Criminology and Criminal Research written by Gian Maria Campedelli and published by Routledge Advances in Criminology. This book was released on 2022 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, 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 Artificial Intelligence (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 non-technical 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. The 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 final 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 an important reading for scholars and students in criminology, criminal justice, sociology and economics, as well as Artificial Intelligence, data sciences and statistics, and computer science.
Download or read book Proceedings of 8th Edition of International Conference on Big Data Data Science 2019 written by Euroscicon and published by EuroScicon. This book was released on 2019-02-24 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Big Data Crime and Social Control written by Aleš Završnik and published by Routledge. This book was released on 2017-09-20 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Methods of Criminology and Criminal Justice Research written by Mathieu Deflem and published by Emerald Group Publishing. This book was released on 2019-08-26 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Knowledge Discovery in the Social Sciences written by Xiaoling Shu and published by University of California Press. This book was released on 2020-02-04 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries
Download or read book The SAGE Dictionary of Criminology written by Eugene McLaughlin and published by SAGE. This book was released on 2019-04-08 with total page 1188 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook on Risk and Need Assessment written by Faye S. Taxman and published by Routledge. This book was released on 2016-11-10 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Researching Cybercrimes written by Anita Lavorgna and published by Springer Nature. This book was released on 2021-07-29 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Predictive Policing and Artificial Intelligence written by John McDaniel and published by Routledge. This book was released on 2021-02-25 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited text draws together the insights of numerous worldwide eminent academics to evaluate the condition of predictive policing and artificial intelligence (AI) as interlocked policy areas. Predictive and AI technologies are growing in prominence and at an unprecedented rate. Powerful digital crime mapping tools are being used to identify crime hotspots in real-time, as pattern-matching and search algorithms are sorting through huge police databases populated by growing volumes of data in an eff ort to identify people liable to experience (or commit) crime, places likely to host it, and variables associated with its solvability. Facial and vehicle recognition cameras are locating criminals as they move, while police services develop strategies informed by machine learning and other kinds of predictive analytics. Many of these innovations are features of modern policing in the UK, the US and Australia, among other jurisdictions. AI promises to reduce unnecessary labour, speed up various forms of police work, encourage police forces to more efficiently apportion their resources, and enable police officers to prevent crime and protect people from a variety of future harms. However, the promises of predictive and AI technologies and innovations do not always match reality. They often have significant weaknesses, come at a considerable cost and require challenging trade- off s to be made. Focusing on the UK, the US and Australia, this book explores themes of choice architecture, decision- making, human rights, accountability and the rule of law, as well as future uses of AI and predictive technologies in various policing contexts. The text contributes to ongoing debates on the benefits and biases of predictive algorithms, big data sets, machine learning systems, and broader policing strategies and challenges. Written in a clear and direct style, this book will appeal to students and scholars of policing, criminology, crime science, sociology, computer science, cognitive psychology and all those interested in the emergence of AI as a feature of contemporary policing.
Download or read book Handbook of Computational Social Science Volume 1 written by Uwe Engel and published by Taylor & Francis. This book was released on 2021-11-10 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field but also encourages growth in new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientifi c and engineering sectors.
