Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 4-28 |
| Number of pages | 25 |
| Journal | Language and Psychoanalysis |
| Volume | 7 |
| Issue number | 2 |
| Early online date | 21 Sept 2018 |
| DOIs | |
| Publication status | Published - 15 Dec 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Fingerprint
Dive into the research topics of 'Core Conflictual Relationship: Text Mining to Discover What and When'. Together they form a unique fingerprint.Research output
- 1 Book
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Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics
Murtagh, F., 7 Sept 2017, Boca Raton, FL: CRC Press. 206 p. (Computer Science & Data Analysis Series)Research output: Book/Report › Book › peer-review
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