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How We Do Things With Words: Analyzing Text as Social and Cultural Data
Dong Nguyen1,2,3, Maria Liakata1,4,5, Simon DeDeo6,7
1Alan Turing Institute, London, United Kingdom.
Frontiers in Artificial Intelligence
|March 18, 2021
Summary
This study explores computational text analysis for social and cultural concepts, offering guidance and promoting interdisciplinary collaboration for richer insights.
Area of Science:
- Computational Social Science
- Digital Humanities
- Text Analysis Methodologies
Background:
- Computational text analysis is increasingly used for social and cultural concepts.
- Discussions often overlook complex challenges inherent in these analyses.
- Interdisciplinary approaches are crucial but not always fully realized.
Purpose of the Study:
- To highlight critical issues in computational text analysis of social and cultural data.
- To provide guiding questions for researchers in this domain.
- To foster greater interdisciplinary collaboration.
Main Methods:
- The study draws on the authors' diverse experiences in computational text analysis.
- It synthesizes insights from varied disciplinary backgrounds and research practices.
- Key questions are formulated based on practical challenges and commonalities observed.
Main Results:
- Identification of complex, often-understated issues in computational text analysis.
- Development of a framework of guiding questions for future research.
- Emphasis on the necessity of bridging disciplinary divides.
Conclusions:
- Computational text analysis of social and cultural concepts requires careful consideration of complex issues.
- A structured approach with guiding questions can improve research quality.
- Interdisciplinary collaboration is essential for advancing the field and unlocking its full potential.
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