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Data Mining Methods For The Content Analyst
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Book Synopsis Data Mining Methods for the Content Analyst by : Kalev Leetaru
Download or read book Data Mining Methods for the Content Analyst written by Kalev Leetaru and published by Routledge. This book was released on 2012-11-12 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: With continuous advancements and an increase in user popularity, data mining technologies serve as an invaluable resource for researchers across a wide range of disciplines in the humanities and social sciences. In this comprehensive guide, author and research scientist Kalev Leetaru introduces the approaches, strategies, and methodologies of current data mining techniques, offering insights for new and experienced users alike. Designed as an instructive reference to computer-based analysis approaches, each chapter of this resource explains a set of core concepts and analytical data mining strategies, along with detailed examples and steps relating to current data mining practices. Every technique is considered with regard to context, theory of operation and methodological concerns, and focuses on the capabilities and strengths relating to these technologies. In addressing critical methodologies and approaches to automated analytical techniques, this work provides an essential overview to a broad innovative field.
Book Synopsis Data Mining Methods for the Content Analyst by : Kalev Leetaru
Download or read book Data Mining Methods for the Content Analyst written by Kalev Leetaru and published by Routledge. This book was released on 2012 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research reference introduces readers to the data mining technologies available for use in content analysis research. Supporting the increasingly popular trend of employing digital analysis methodologies in the humanities, arts, and social sciences, this work provides crucial answers for researchers who are not familiar with data mining approaches and who do not know what they can do, how they work, or how their strengths and weaknesses match up to the strengths and weaknesses of human coded content analysis data. Offering valuable insights and guidance for using automated analytical techniques in content analysis research, this guide will appeal to both novice and experienced researchers throughout the humanities, arts, and social sciences.
Book Synopsis Content Analysis by : Klaus Krippendorff
Download or read book Content Analysis written by Klaus Krippendorff and published by SAGE. This book was released on 2004 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second Edition of Content Analysis: An Introduction to Its Methodology is a definitive sourcebook of the history and core principles of content analysis as well as an essential resource for present and future studies. The book introduces readers to ways of analyzing meaningful matter such as texts, images, voices - that is, data whose physical manifestations are secondary to the meanings that a particular population of people brings to them. Organized into three parts, the book examines the conceptual and methodological aspects of content analysis and also traces several paths through content analysis protocols. The author has completely revised and updated the Second Edition, integrating new information on computer-aided text analysis. The book also includes a practical guide that incorporates experiences in teaching and how to advise academic and commercial researchers. In addition, Krippendorff clarifies the epistemology and logic of content analysis as well as the methods for achieving its aims. Intended as a textbook for advanced undergraduate and graduate students across the social sciences, Content Analysis, Second Edition will also be a valuable resource for practitioners in a variety of disciplines.
Book Synopsis Data Mining Methods for Knowledge Discovery by : Krzysztof J. Cios
Download or read book Data Mining Methods for Knowledge Discovery written by Krzysztof J. Cios and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.
Book Synopsis Data Mining: Concepts and Techniques by : Jiawei Han
Download or read book Data Mining: Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Book Synopsis Content Analysis by : Klaus Krippendorff
Download or read book Content Analysis written by Klaus Krippendorff and published by SAGE. This book was released on 2013 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the First Edition of Content Analysis: An Introduction to Its Methodology, the textual fabric in which contemporary society functions has undergone a radical transformation - namely, the ongoing information revolution. Two decades ago, content analysis was largely known in journalism and communication research, and, to a lesser extent, in the social and psychological sciences. Today, content analysis has become an efficient alternative to public opinion research - a method of tracking markets, political leanings, and emerging ideas, a way to settle legal disputes, and an approach to explore individual human minds. The Third Edition of Content Analysis remains the definitive sourcebook of the history and core principles of content analysis as well as an essential resource for present and future studies. The book introduces readers to ways of analyzing meaningful matter such as texts, images, voices - that is, data whose physical manifestations are secondary to the meanings that a particular population of people brings to them. Organized into three parts, the book examines the conceptual and methodological aspects of content analysis and also traces several paths through content analysis protocols. The author has completely revised and updated the Third Edition, integrating new information on computer-aided text analysis and social media. The book also includes a practical guide that incorporates experiences in teaching and how to advise academic and commercial researchers. In addition, Krippendorff clarifies the epistemology and logic of content analysis as well as the methods for achieving its aims.
Book Synopsis Data Mining Techniques by : Michael J. A. Berry
Download or read book Data Mining Techniques written by Michael J. A. Berry and published by John Wiley & Sons. This book was released on 2004-04-09 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.
Book Synopsis Handbook of Statistical Analysis and Data Mining Applications by : Robert Nisbet
Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Robert Nisbet and published by Elsevier. This book was released on 2017-11-09 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Book Synopsis Contemporary Research Methods and Data Analytics in the News Industry by : Gibbs, William J.
Download or read book Contemporary Research Methods and Data Analytics in the News Industry written by Gibbs, William J. and published by IGI Global. This book was released on 2015-07-01 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of digital technologies has changed the news and publishing industries drastically. While shrinking newsrooms may be a concern for many, journalists and publishing professionals are working to reorient their skills and capabilities to employ technology for the purpose of better understanding and engaging with their audiences. Contemporary Research Methods and Data Analytics in the News Industry highlights the research behind the innovations and emerging practices being implemented within the journalism industry. This crucial, industry-shattering publication focuses on key topics in social media and video streaming as a new form of media communication as well the application of big data and data analytics for collecting information and drawing conclusions about the current and future state of print and digital news. Due to significant insight surrounding the latest applications and technologies affecting the news industry, this publication is a must-have resource for journalists, analysts, news media professionals, social media strategists, researchers, television news producers, and upper-level students in journalism and media studies. This timely industry resource includes key topics on the changing scope of the news and publishing industries including, but not limited to, big data, broadcast journalism, computational journalism, computer-mediated communication, data scraping, digital media, news media, social media, text mining, and user experience.
Book Synopsis Descriptive Data Mining by : David L. Olson
Download or read book Descriptive Data Mining written by David L. Olson and published by Springer. This book was released on 2019-05-06 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Diagnostic analytics can apply analysis to sensor input to direct control systems automatically. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on descriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic software support to data visualization. Chapter 3 covers fundamentals of market basket analysis, and Chapter 4 provides demonstration of RFM modeling, a basic marketing data mining tool. Chapter 5 demonstrates association rule mining. Chapter 6 is a more in-depth coverage of cluster analysis. Chapter 7 discusses link analysis. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.
Author :Claudio Cioffi-Revilla Publisher :Springer Science & Business Media ISBN 13 :1447156617 Total Pages :320 pages Book Rating :4.4/5 (471 download)
Book Synopsis Introduction to Computational Social Science by : Claudio Cioffi-Revilla
Download or read book Introduction to Computational Social Science written by Claudio Cioffi-Revilla and published by Springer Science & Business Media. This book was released on 2013-12-31 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.
Book Synopsis Computer Supported Qualitative Research by : António Pedro Costa
Download or read book Computer Supported Qualitative Research written by António Pedro Costa and published by Springer Nature. This book was released on 2019-09-16 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The World Conference on Qualitative Research (WCQR) is an annual event that aims to bring together researchers, academics and professionals, promoting the sharing and discussion of knowledge, new perspectives, experiences and innovations on the field of Qualitative Research. This book includes a selection of the articles accepted for presentation and discussion at WCQR2019, held in Porto, Portugal, October 16-18, 2019. WCQR2019 featured four main application fields (Education, Health, Social Sciences, and Engineering/Technology) and seven main subjects: Rationale and Paradigms of Qualitative Research; Systematization of Approaches with Qualitative Studies; Qualitative and Mixed Methods Research; Data Analysis Types; Innovative Processes of Qualitative Data Analysis; Qualitative Research in Web Context; Qualitative Analysis with Software Support. The book is a valuable resource for everyone interested in Qualitative Research with emphasis on Computer Assisted Qualitative Data Analysis.
Book Synopsis Data Mining Methods and Models by : Daniel T. Larose
Download or read book Data Mining Methods and Models written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2006-02-02 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-04-18 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "…full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.
Book Synopsis Rethinking Research Methods in an Age of Digital Journalism by : Michael Karlsson
Download or read book Rethinking Research Methods in an Age of Digital Journalism written by Michael Karlsson and published by Routledge. This book was released on 2018-10-18 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital infrastructure of media production, dissemination and consumption is becoming increasingly complex, presenting the challenge of how we should research the digital journalism environment. Digital journalism takes many forms – we therefore need to revise, improve, adjust and even invent methods to understand emerging forms of journalism. In this book, scholars at the forefront of methodological innovations in digital journalism research share their insights on how to collect, process and analyse the diverse expressions of digital journalism, including online news, search results, hyperlinks and social media posts. As digital journalism content often comes in the form of big data, many of these new approaches depart from the traditional methods used in media research in significant ways. As we move towards new ways of understanding digital journalism, the methods developed for such purposes also need to be grounded in scientific rigour. This book aims to share some of the emerging processes by which these methods, tools and approaches are designed, implemented and validated. As such, this book not only constitutes a benchmark for thinking about research methods in digital journalism, it also provides an entry point for graduate students and seasoned scholars aiming to do research on digital journalism. This book was originally published as a special issue of Digital Journalism.
Book Synopsis Data Mining the Web by : Zdravko Markov
Download or read book Data Mining the Web written by Zdravko Markov and published by John Wiley & Sons. This book was released on 2007-04-06 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).
Book Synopsis The Global Politics of Science and Technology - Vol. 2 by : Maximilian Mayer
Download or read book The Global Politics of Science and Technology - Vol. 2 written by Maximilian Mayer and published by Springer. This book was released on 2014-08-20 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: An increasing number of scholars have begun to see science and technology as relevant issues in International Relations (IR), acknowledging the impact of material elements, technical instruments, and scientific practices on international security, statehood, and global governance. This two-volume collection brings the debate about science and technology to the center of International Relations. It shows how integrating science and technology translates into novel analytical frameworks, conceptual approaches and empirical puzzles, and thereby offers a state-of-the-art review of various methodological and theoretical ways in which sciences and technologies matter for the study of international affairs and world politics. The authors not only offer a set of practical examples of research frameworks for experts and students alike, but also propose a conceptual space for interdisciplinary learning in order to improve our understanding of the global politics of science and technology. The second volume raises a plethora of issue areas, actors, and cases under the umbrella notion techno-politics. Distinguishing between interactional and co-productive perspectives, it outlines a toolbox of analytical frameworks that transcend technological determinism and social constructivism.
