Summary
Chapters
Video Info
SAGE Social Science Communication Manager, Michael Todd, introduces the webinar, quantitative text analysis (QTA) for social scientists, and speaker Nicole Rae Baerg, PhD, Lecturer in the department of Government at the University of Essex, Nicole Rae Baerg, discusses what QTA is and what it isn't, the basic QTA process, what assumptions must be made, text as the new frontier, what should be considered, key features of QTA, examples of QTA in every day life, its application to political texts, whether it can be scaled, using a social science approach to QTA, and resources for further information. A Q&A session follows touching on ethical issues, software, working with older texts, generalizing the findings, replication of results, its use in mixed methods, and working with multiple languages.
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Chapter 1: Introduction to Webinar and to Nicole Rae Baerg
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Chapter 2: What is, and isn't, Quantitative Textual Analysis?
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Chapter 3: What is the Basic QTA Process and What Assumptions Must be Made to Quantitatively Analyze Text??
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Chapter 4: Is Text the New Frontier? What should be Considered?
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Chapter 5: What are Some of the Key Features of QTA?
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Chapter 6: What are Some Examples of Every Day QTA and How can QTA be Applied to Political Texts?
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Chapter 7: Can Quantitative Textual Analysis be Scaled?
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Chapter 8: Why is a Social Science Approach to Textual Analysis Important and can You Give an Example?
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Chapter 9: What are Some Resources for Further Information?
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Chapter 10: Q&A: What are Some of the Central Ethical Issues About This Kind of Research?
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Chapter 11: Q&A: What Software do You Use?
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Chapter 12: Q&A: What are Some of the Limitations When Working With Older Texts, Such as 19th Century Newspapers?
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Chapter 13: Q&A: What would be a Good Practice to Generalize Your Findings?
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Chapter 14: Q&A: Can This Research be Replicated?
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Chapter 15: Q&A: How can Similarly Sized Texts with Different Contexts be Differentiated and Validated?
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Chapter 16: Q&A: Can Quantitative Textual Analysis be Used in Mixed Methods? What Techniques do You See as Helping in Content or Topic Analysis on a Computational Basis?
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Chapter 17: Q&A: What Challenges did You Find in Compiling and Comparing Textual Data Across Multiple Languages?
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