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Qualitative Text Analysis A Guide to Methods Practice Using Software 1st Edition by Udo Kuckartz ISBN 1446267741 9781446267745

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Qualitative Text Analysis A Guide to Methods Practice Using Software Udo Kuckartz Digital Instant Download

Author(s): Udo Kuckartz
ISBN(s): 9781446267745, 1446267741
Edition: Hardcover
File Details: PDF, 3.53 MB
Year: 2014
Language: english
SKU: EB-10437180 Category: Tag:

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ISBN 10: 1446267741 
ISBN 13: 9781446267745
Author: Udo Kuckartz

How can you analyse narratives, interviews, field notes, or focus group data?

Qualitative text analysis is ideal for these types of data and this textbook provides a hands-on introduction to the method and its theoretical underpinnings. It offers step-by-step instructions for implementing the three principal types of qualitative text analysis: thematic, evaluative, and type-building. Special attention is paid to how to present your results and use qualitative data analysis software packages, which are highly recommended for use in combination with qualitative text analysis since they allow for fast, reliable, and more accurate analysis. The book shows in detail how to use software, from transcribing the verbal data to presenting and visualizing the results.

The book is intended for Masters and Doctoral students across the social sciences and for all researchers concerned with the systematic analysis of texts of any kind.

Qualitative Text Analysis A Guide to Methods Practice Using Software 1st Table of contents:

Part I: Introduction to Qualitative Text Analysis

Chapter 1: What is Qualitative Text Analysis?

  • Defining Qualitative Research

  • The Role of Text in Qualitative Research

  • Historical Development of Textual Analysis

  • Why Qualitative Text Analysis Matters

Chapter 2: Theoretical Foundations of Qualitative Text Analysis

  • Theoretical Approaches: From Structuralism to Post-Structuralism

  • Hermeneutics and Phenomenology

  • Critical Discourse Analysis (CDA)

  • Grounded Theory and Textual Analysis

  • Interpretive Paradigms in Qualitative Research

Chapter 3: Designing a Qualitative Text Analysis Study

  • Formulating Research Questions

  • Selecting Textual Data

  • Ethical Considerations in Textual Research

  • Planning and Structuring Your Analysis

Part II: Methods of Qualitative Text Analysis

Chapter 4: Manual Techniques in Qualitative Text Analysis

  • Close Reading and Thematic Analysis

  • Content Analysis: Manual vs. Computer-Assisted Approaches

  • Discourse Analysis: Language and Power

  • Narrative Analysis: Identifying Stories in Texts

  • Textual Coding and Categorization

Chapter 5: Computer-Assisted Qualitative Data Analysis (CAQDAS)

  • Introduction to CAQDAS Software

  • Benefits and Limitations of Using Software

  • Popular CAQDAS Tools: NVivo, ATLAS.ti, MAXQDA, and Others

  • Preparing Data for Software Analysis

Chapter 6: Text Mining and Natural Language Processing (NLP)

  • Basics of Text Mining

  • Sentiment Analysis and Word Frequency

  • Lexical Analysis: Word Clouds, Concordances, and Collocates

  • The Role of NLP in Qualitative Text Analysis

  • Using NLP to Process Large Text Corpora

Part III: Using Software in Qualitative Text Analysis

Chapter 7: Getting Started with NVivo

  • Introduction to NVivo Software

  • Setting Up a Project in NVivo

  • Importing and Organizing Text Data

  • Coding Text and Generating Queries

  • Visualizing Data with NVivo

Chapter 8: Using ATLAS.ti for Qualitative Text Analysis

  • Introduction to ATLAS.ti Software

  • Importing Text and Building a Project

  • Applying Codes and Annotations

  • Performing Query-Based Analysis

  • Visual Tools: Networks, Maps, and Diagrams

Chapter 9: MAXQDA: An Overview of Key Features

  • Setting Up a Project in MAXQDA

  • Coding and Categorization in MAXQDA

  • Analyzing Data: Using the MAXQDA Query Functions

  • Text Search and Visualization Tools

  • Combining Qualitative and Quantitative Analysis

Chapter 10: Other Software and Tools for Text Analysis

  • Overview of Other Software (e.g., Dedoose, QDA Miner)

  • Open-Source Tools for Qualitative Analysis

  • Comparative Analysis of Software Features

  • Choosing the Right Tool for Your Research

Part IV: Advanced Topics and Applications

Chapter 11: Analyzing Large Text Datasets

  • Techniques for Managing and Analyzing Large Textual Data

  • Data Sampling and Filtering Techniques

  • Text Mining and Machine Learning Approaches

  • Case Studies in Large-Scale Text Analysis

Chapter 12: Mixed Methods in Qualitative Text Analysis

  • Combining Qualitative and Quantitative Approaches

  • Using Software for Mixed Methods Research

  • Challenges and Opportunities in Mixed Methods Analysis

  • Case Studies of Mixed Methods Text Analysis

Chapter 13: Visualizing Qualitative Textual Data

  • Importance of Visualization in Qualitative Research

  • Common Types of Visualizations: Word Clouds, Code Maps, Graphs

  • Using Software to Create Effective Visualizations

  • Interpreting Visual Data and Communicating Findings

Chapter 14: Writing and Presenting Qualitative Text Analysis Findings

  • Structuring Your Analysis and Results

  • Presenting Findings: From Data to Argument

  • Writing for Academic and Non-Academic Audiences

  • Ethical Reporting and Transparency

Part V: Future Directions and Reflections

Chapter 15: Challenges and Opportunities in Qualitative Text Analysis

  • The Impact of Big Data and Digital Texts

  • The Role of AI and Automation in Qualitative Analysis

  • Ethical Issues and Data Privacy in Textual Research

  • Future Trends in Qualitative Text Analysis

Chapter 16: Conclusion: Reflecting on the Practice of Qualitative Text Analysis

  • Recap of Key Insights

  • The Evolving Role of Qualitative Analysis in Social Science Research

  • Final Thoughts and Recommendations for Researchers

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Tags: Udo Kuckartz, Analysis, Practice Using