Data Mining Methods for the Content Analyst

Data Mining Methods for the Content Analyst
Author: Kalev Leetaru
Publisher: Routledge
Total Pages: 122
Release: 2012
Genre: Computers
ISBN: 0415895138

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.

Data Mining Methods and Models

Data Mining Methods and Models
Author: Daniel T. Larose
Publisher: John Wiley & Sons
Total Pages: 340
Release: 2006-02-02
Genre: Computers
ISBN: 0471756474

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.

Data Mining and Machine Learning

Data Mining and Machine Learning
Author: Mohammed J. Zaki
Publisher: Cambridge University Press
Total Pages: 779
Release: 2020-01-30
Genre: Business & Economics
ISBN: 1108473989

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Content Analysis

Content Analysis
Author: Klaus Krippendorff
Publisher: SAGE
Total Pages: 457
Release: 2013
Genre: Language Arts & Disciplines
ISBN: 1412983150

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.

The Content Analysis Guidebook

The Content Analysis Guidebook
Author: Kimberly A. Neuendorf
Publisher: SAGE
Total Pages: 457
Release: 2017
Genre: Language Arts & Disciplines
ISBN: 1412979471

Content analysis is a complex research methodology. This book provides an accessible text for upper level undergraduates and graduate students, comprising step-by-step instructions and practical advice.

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
Author: Ken Yale
Publisher: Elsevier
Total Pages: 824
Release: 2017-11-09
Genre: Mathematics
ISBN: 0124166458

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

Data Mining Methods for Knowledge Discovery

Data Mining Methods for Knowledge Discovery
Author: Krzysztof J. Cios
Publisher: Springer Science & Business Media
Total Pages: 508
Release: 2012-12-06
Genre: Computers
ISBN: 1461555892

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.

An Introduction to Text Mining

An Introduction to Text Mining
Author: Gabe Ignatow
Publisher: SAGE Publications
Total Pages: 345
Release: 2017-09-22
Genre: Computers
ISBN: 150633699X

Students in social science courses communicate, socialize, shop, learn, and work online. When they are asked to collect data for course projects they are often drawn to social media platforms and other online sources of textual data. There are many software packages and programming languages available to help students collect data online, and there are many texts designed to help with different forms of online research, from surveys to ethnographic interviews. But there is no textbook available that teaches students how to construct a viable research project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives. Gabe Ignatow and Rada F. Mihalcea's new text An Introduction to Text Mining will be a starting point for undergraduates and first-year graduate students interested in collecting and analyzing textual data from online sources, and will cover the most critical issues that students must take into consideration at all stages of their research projects, including: ethical and philosophical issues; issues related to research design; web scraping and crawling; strategic data selection; data sampling; use of specific text analysis methods; and report writing.

Computer Supported Qualitative Research

Computer Supported Qualitative Research
Author: António Pedro Costa
Publisher: Springer Nature
Total Pages: 314
Release: 2019-09-16
Genre: Technology & Engineering
ISBN: 3030317870

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.