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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
References
Abbott, H. P.
(2002) The
Cambridge introduction to narrative. Cambridge University Press.
Andrade, S. B., & Andersen, D.
(2020) Digital
story grammar: A quantitative methodology for narrative analysis. International Journal of
Social Research
Methodology, 231, 405–421. 
Andrushchenko, M., Sandberg, K., Turunen, R., Marjanen, J., Hatavara, M., Kurunmäki, J., Nummenmaa, T., Hyvärinen, M., Teräs, K., Peltonen, J., & Nummenmaa, J.
(2021) Using
parsed and annotated corpora to analyze parliamentarians’ talk in Finland. Journal of the
Association for Information Science and
Technology, 73(2), 288–302.
Bögel, T., Strötgen, J., & Gertz, M.
(2015) A
hybrid approach to extract temporal signals from
narratives. In Proceedings of the International Conference of the
German Society for Computational Linguistics and Language
Technology (pp. 106–107). [URL]
Carroll, N.
(2001) On
the narrative connection. In W. van Peer & S. Chatman (Eds.), New
perspectives on narrative
perspective (pp. 21–41). State University of New York Press.
Cohn, D.
(1978) Transparent
minds: Narrative modes for presenting consciousness in fiction. Princeton University Press.
Eisenberg, J. D., & Finlayson, M. A.
(2016) Automatic
identification of narrative diegesis and point of
view. In Proceedings of 2nd Workshop on Computing News
Storylines (pp. 36–46). Association for Computational Linguistics.
Ek, A., & Wiren, M.
Fludernik, M.
(1996) Towards
a ‘natural’ narratology. Routledge.
Genette, G.
(1980) Narrative
discourse revisited. Cornell University Press.
Hatavara, M., & Mildorf, J.
(2017) Fictionality,
narrative models, and vicarious
storytelling. Style, 511, 391–408.
Haverinen, K., Nyblom, J., Viljanen, T., Laippala, V., Kohonen, S., Missilä, A., Ojala, S., Salakoski, T., & Ginter, F.
(2014) Building
the essential resources for Finnish: The Turku dependency treebank. Language Resources and
Evaluation,
48
(3), 493–531.
Herman, D.
(2002) Story
logic: Problems and possibilities of narrative. Nebraska University Press.
(2009) Basic
elements of narrative. Wiley-Blackwell.
Labov, W., & Waletzky, J.
(1997/1967) Narrative
analysis: Oral versions of personal experience. Journal of Narrative and Life
History, 7(1–4), 3–38. (Reprinted
from Essays on the verbal and visual arts: proceedings of the 1966 annual spring meeting of the American Ethnological
Society ed. by June Helm, Seattle: University of Washington Press 1967).
Lin, C., Wright-Bettner, K., Miller, T., Bethard, S., Dligach, D., Palmer, M., Martin, J. H., & Savova, G.
(2020) Defining
and learning refined temporal relations in the clinical
narrative. In Proceedings of the 11th International Workshop on
Health Text Mining and Information
Analysis (pp. 104–114). Association for Computational Linguistics.
Lindstedt, J.
(2000) The
perfect – aspectual, temporal and evidential. In Ö. Dahl (Ed.), Tense
and aspect in the languages of
Europe (pp. 259–277). Mouton de Gruyter.
Mani, I.
(2014) Computational
narratology. In P. Hühn, J. C. Meister, J. Pier, & W. Schmid (Eds.), Handbook
of
narratology (pp. 84–92). De Gruyter, Inc.
Martin, J. R., & Rose, D.
(2008) Genre
relations. Mapping culture. Equinox.
Miller, B., & Park, J. S.
Pallaskallio, R.
(2013) Kertova tempus: finiittiverbin aikamuodon valinta suomenkielisissä katastrofiuutisteksteissä
1860–2004 [Narrative usage of tense in Finnish disaster news texts
1860–2004]. University of Helsinki, Faculty of Arts, Department of Finnish, Finno-Ugrian and Scandinavian Studies. [URL]
Piper, A., So, R. J., & Bamman, D.
(2021) Narrative
theory for computational narrative understanding. In Proceedings of
the 2021 Conference on
EMNLP (pp. 298–311). Association for Computational Linguistics.
Prince, G.
(1982) Narratology.
The form and functioning of narrative. Mouton.
(1987) A
dictionary of narratology. University of Nebraska Press.
Rappaport Hovav, M., & Levin, B.
(2015) The
syntax-semantics interface: Semantic roles and syntactic
arguments. In S. Lappin & C. Fox (Eds.), The
handbook of contemporary semantic
theory (pp. 593–624). 2nd
ed. Wiley Blackwell.
Reiter, N., Willand, M., & Gius, E.
(2019) A
shared task for the digital humanities chapter 1: Introduction to annotation, narrative levels and shared
tasks. Journal of Cultural
Analytics 4(3).
Sagae, K., Gordon, A. S., Dehghani, M., Metke, M., Kim, J. S., Gimbel, S. I., Tipper, C., Kaplan, J., & Immordino-Yang, M. H.
(2013) A
Data-Driven Approach for Classification of Subjectivity in Personal
Narratives. In M. A. Finlayson, B. Fisseni, B. Löwe, & J. C. Meister (Eds.), Workshop
on Computational Models of Narrative
2013 (pp. 198–213). Schloss Dagstuhl – Leibniz-Zentrum für Informatik.
Sudhahar, S., Franzosi, R., & Cristianini, N.
(2011) Automating
quantitative narrative analysis of news data. In T. Diethe, J. Balcázar, J. Shawe-Taylor, & C. Tîrnăucă (Eds.), JMLR:
Workshop and Conference
Proceedings 171, 63–71. [URL]
Tammi, P.
(2006) Against
narrative. A boring story. Partial
Answers, 4(2), 19–40.
Virtanen, T.
(1992) Issues
of text typology: Narrative – a ‘basic’ type of
text? Text, 121, 293–310.
VoDe
Corpora
(2021) Parliamentary text corpus. Voices of Democracy Project,
Plenary sessions of the parliament of Finland from 1980 to 2021. Interview corpus. Voices of
Democracy Project, 404 veteran parliamentarians’ interviews. Both corpora grammatically parsed. Requires separate access
rights.
Voutilainen, E. R. J.
(2017) The
regulation of linguistic quality in the official speech-to-text reports of the Finnish
parliament. CoMe: Studies on Communication and Linguistic and Cultural
Mediation, 61–73. [URL]
White, H.
(1987) The
content of the form. Narrative discourse and historical representation. The Johns Hopkins University Press.
Yang, H., & Garibaldi, J. M.
(2015) Automatic
detection of protected health information from clinic narratives. Journal of Biomedical
Informatics, 581, S30–S38.
Zhang, H., Boons, F., & Batista-Navarro, R.
(2019) Whose
story is it anyway? Automatic extraction of accounts from news articles. Information Processing
and
Management, 56(5), 1837–1848.