1. ZHAW digitalcollection
  2. Angewandte Linguistik
  3. Publikationen
  4. Publikationen Angewandte Linguistik
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-24539
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMahlow, Cerstin-
dc.contributor.authorUlasik, Malgorzata Anna-
dc.contributor.authorTuggener, Don-
dc.date.accessioned2022-03-10T15:28:30Z-
dc.date.available2022-03-10T15:28:30Z-
dc.date.issued2022-01-01-
dc.identifier.issn0922-4777de_CH
dc.identifier.issn1573-0905de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/24539-
dc.descriptionOnline first, part of special issue "Methods for understanding writing process by analysis of writing timecourse" Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)de_CH
dc.description.abstractProducing written texts is a non-linear process: in contrast to speech, writers are free to change already written text at any place at any point in time. Linguistic considerations are likely to play an important role, but so far, no linguistic models of the writing process exist. We present an approach for the analysis of writing processes with a focus on linguistic structures based on the novel concepts of transforming sequences, text history, and sentence history. The processing of raw keystroke logging data and the application of natural language processing tools allows for the extraction and filtering of product and process data to be stored in a hierarchical data structure. This structure is used to re-create and visualize the genesis and history for a text and its individual sentences. Focusing on sentences as primary building blocks of written language and full texts, we aim to complement established writing process analyses and, ultimately, to interpret writing timecourse data with respect to linguistic structures. To enable researchers to explore this view, we provide a fully functional implementation of our approach as an open-source software tool and visualizations of the results. We report on a small scale exploratory study in German where we used our tool. The results indicate both the feasibility of the approach and that writers actually revise on a linguistic level. The latter confirms the need for modeling written text production from the perspective of linguistic structures beyond the word level.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofReading and Writingde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectWriting processde_CH
dc.subjectKeystroke-loggingde_CH
dc.subjectTransforming sequencede_CH
dc.subjectText historyde_CH
dc.subjectSentence historyde_CH
dc.subjectWritten text productionde_CH
dc.subjectLinguistic modelingde_CH
dc.subject.ddc808: Rhetorik und Schreibende_CH
dc.titleExtraction of transforming sequences and sentence histories from writing process data : a first step towards linguistic modeling of writingde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementAngewandte Linguistikde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitCentre for Artificial Intelligence (CAI)de_CH
zhaw.organisationalunitInstitute of Language Competence (ILC)de_CH
dc.identifier.doi10.1007/s11145-021-10234-6de_CH
dc.identifier.doi10.21256/zhaw-24539-
zhaw.funding.euNode_CH
zhaw.issue2de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end482de_CH
zhaw.pages.start443de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume37de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDigital Linguisticsde_CH
zhaw.webfeedNatural Language Processingde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Angewandte Linguistik

Files in This Item:
File Description SizeFormat 
2022_Mahlow-etal_Transforming-sequence-sentence-histories-extraction.pdf4.5 MBAdobe PDFThumbnail
View/Open
Show simple item record
Mahlow, C., Ulasik, M. A., & Tuggener, D. (2022). Extraction of transforming sequences and sentence histories from writing process data : a first step towards linguistic modeling of writing. Reading and Writing, 37(2), 443–482. https://doi.org/10.1007/s11145-021-10234-6
Mahlow, C., Ulasik, M.A. and Tuggener, D. (2022) ‘Extraction of transforming sequences and sentence histories from writing process data : a first step towards linguistic modeling of writing’, Reading and Writing, 37(2), pp. 443–482. Available at: https://doi.org/10.1007/s11145-021-10234-6.
C. Mahlow, M. A. Ulasik, and D. Tuggener, “Extraction of transforming sequences and sentence histories from writing process data : a first step towards linguistic modeling of writing,” Reading and Writing, vol. 37, no. 2, pp. 443–482, Jan. 2022, doi: 10.1007/s11145-021-10234-6.
MAHLOW, Cerstin, Malgorzata Anna ULASIK und Don TUGGENER, 2022. Extraction of transforming sequences and sentence histories from writing process data : a first step towards linguistic modeling of writing. Reading and Writing. 1 Januar 2022. Bd. 37, Nr. 2, S. 443–482. DOI 10.1007/s11145-021-10234-6
Mahlow, Cerstin, Malgorzata Anna Ulasik, and Don Tuggener. 2022. “Extraction of Transforming Sequences and Sentence Histories from Writing Process Data : A First Step towards Linguistic Modeling of Writing.” Reading and Writing 37 (2): 443–82. https://doi.org/10.1007/s11145-021-10234-6.
Mahlow, Cerstin, et al. “Extraction of Transforming Sequences and Sentence Histories from Writing Process Data : A First Step towards Linguistic Modeling of Writing.” Reading and Writing, vol. 37, no. 2, Jan. 2022, pp. 443–82, https://doi.org/10.1007/s11145-021-10234-6.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.