lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Core conflictual relationship: text mining to discover what and when
University of Huddersfield, UK.ORCID iD: 0000-0002-0589-6892
Linnaeus University, Faculty of Technology, Department of Mathematics. (ICMM)
2018 (English)In: Language and Psychoanalysis, ISSN 2049-324X, Vol. 7, no 2, p. 4-28Article in journal (Refereed) Published
Abstract [en]

Following detailed presentation of the Core Conflictual Relationship Theme (CCRT), there is the objective of relevant methods for what has been described as verbalization and visualization of data. Such is also termed data mining and text mining, and knowledge discovery in data. The Correspondence Analysis methodology, also termed Geometric Data Analysis, is shown in a case study to be comprehensive and revealing. Quite innovative here is how the analysis process is structured. For both illustrative and revealing aspects of the case study here, relatively extensive dream reports are used. The dream reports are from an open source repository of dream reports, and the current study proposes a possible framework for the analysis of dream report narratives, and further, how such an analysis could be relevant within the psychotherapeutic context. This Geometric Data Analysis here confirms the validity of CCRT method.

Place, publisher, year, edition, pages
Edinburgh: University of Edinburgh , 2018. Vol. 7, no 2, p. 4-28
National Category
Other Computer and Information Science Bioinformatics (Computational Biology)
Research subject
Computer and Information Sciences Computer Science; Natural Science
Identifiers
URN: urn:nbn:se:lnu:diva-83292DOI: 10.7565/landp.v7i2.1585ISI: 000454105200001Scopus ID: 2-s2.0-85057740070OAI: oai:DiVA.org:lnu-83292DiVA, id: diva2:1317870
Available from: 2019-05-24 Created: 2019-05-24 Last updated: 2019-05-27Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Murtagh, Fionn
By organisation
Department of Mathematics
Other Computer and Information ScienceBioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 8 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf