Word Association Thematic Analysis
eBook - PDF

Word Association Thematic Analysis

A Social Media Text Exploration Strategy

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Word Association Thematic Analysis

A Social Media Text Exploration Strategy

About this book

Many research projects involve analyzing sets of texts from the social web or elsewhere to get insights into issues, opinions, interests, news discussions, or communication styles. For example, many studies have investigated reactions to Covid-19 social distancing restrictions, conspiracy theories, and anti-vaccine sentiment on social media. This book describes word association thematic analysis, a mixed methods strategy to identify themes within a collection of social web or other texts. It identifies these themes in the differences between subsets of the texts, including female vs. male vs. nonbinary, older vs. newer, country A vs. country B, positive vs. negative sentiment, high scoring vs. low scoring, or subtopic A vs. subtopic B. It can also be used to identify the differences between a topic-focused collection of texts and a reference collection. The method starts by automatically finding words that are statistically significantly more common in one subset than another, thenidentifies the context of these words and groups them into themes. It is supported by the free Windows-based software Mozdeh for data collection or importing and for the quantitative analysis stages. This book explains the word association thematic analysis method, with examples, and gives practical advice for using it. It is primarily intended for social media researchers and students, although the method is applicable to any collection of short texts.

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Yes, you can access Word Association Thematic Analysis by Michael Thelwall in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Networking. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Copyright Page
  3. Title Page
  4. Contents
  5. Acknowledgments
  6. Introduction
  7. Data Collection with Mozdeh
  8. Word Association Detection: Term Identification
  9. Word Association Contextualization: Term Meaning and Context
  10. Word Association Thematic Analysis: Theme Detection
  11. Word Association Thematic Analysis Examples
  12. Comparison Between WATA and Other Methods
  13. Ethics
  14. Project Planning
  15. 3.7 Summary
  16. References
  17. Author Biography