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Narrative Inquiry: Online-First ArticlesComputational recognition of narratives
Applying narratological definitions to the analysis of political language use
Computational recognition of narratives, if successful, would find innumerable applications with large digitized
datasets. Systematic identification of narratives in the text flow could significantly contribute to such pivotal questions as
where, when, and how narratives are employed. This paper discusses an approach to extract narratives from two datasets, Finnish
parliamentary records (1980–2021) and oral history interviews with former Finnish MPs (1988–2018). Our study was based on an
iterative approach, proceeding from original expert readings to a rule-based, computational approach that was elaborated with the
help of annotated samples and annotation scheme. Annotated samples and computationally found extracts were compared, and a good
correspondence was found. In this paper, we exhibit and compare the results from annotation and rule-based approach, and discuss
examples of correctly and incorrectly found narrative sections. We consider that all attempts at recognizing and extracting
narratives are definition dependent, and feed back to narrative theory.
Keywords: narrative theory, recognition of narratives, computational approach, rule-based searches, annotation, digital humanism, parliamentary records, applied narratology
Article outline
- Introduction
- Our database of parsed data and a search tool
- Narrative definitions operationalized
- The annotation scheme and procedure
- Narrative detection algorithm
- Quantitative results
- Qualitative analysis of the results
- Conclusion
-
References
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