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From CAQDAS to Text Mining. The Domain Ontology as a Model of Knowledge Representation About Qualitative Research Practices

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Computer Supported Qualitative Research (WCQR 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1068))

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Abstract

The nature of qualitative research practices is multiparadigmaticity which creates coexistence of different research and analytical approaches. This paper is a methodological reflection on how the process of qualitative data analysis is developing, moving from traditional CAQDAS coding procedures through Content Analysis dictionary-based approach towards the textual data exploration for knowledge discovery in corpora using Natural Language Processing and Text Mining procedures. This change is described on the example of the process of analyzing and discovering the ways through which qualitative research practices are conceptualized and represented in the vivid language of scholarly articles. Taking into account the problem of a “curse of abundance” in the present-day field of qualitative research I try to organize and articulate these practices in a legible system of knowledge representation employing the information concept of domain ontology. In the process of building the ontology of the contemporary field of qualitative research practices, I link know-how drawn from sociology, social science computing, NLP and text mining, digital humanities and corpus linguistics.

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Notes

  1. 1.

    The domain ontology as a model of knowledge representation about the contemporary field of qualitative research is the project funded by Polish National Science Center (Competition: OPUS 12; Panel Description: HS6_13: Theoretical sociology, methodological orientations and variants of empirical research). The project duration is 2017–2020.

  2. 2.

    Serendipity is used as a sociological method in grounded theory, building on ideas by sociologist Robert K. Merton, who referred to the “serendipity pattern” as the fairly common experience of observing an unanticipated, anomalous and strategic datum which becomes the occasion for developing a new theory or for extending an existing theory.

  3. 3.

    At present exploration KDD covers different types of analytical procedures i.e. descriptive analysis, matrix and cross-tabs analysis, discovery of association or inductive rules, classification techniques, grouping techniques (factor analysis, cluster analysis, k-means, two-stage grouping), prediction and statistical analysis (i.e. logistic regression, discrimination), discovering sequence patterns, searching for deviations, anomalies, traditional searching and content extraction etc. They are connected not only with the understanding of the language of data and the content of documents but also with the skill of their multidimensional analysis, synthesis of knowledge, meaning or interpretation.

  4. 4.

    Nowadays, the word ontology is used in a lot of diverse research fields including natural language processing, information retrieval, electronic commerce, Web Semantic, software component specification and information systems integration. In this context, some ontology models and languages have been developed in the last decade.

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Authors and Affiliations

  1. Institute of Sociology, CAQDAS TM Lab, Jagiellonian University, ul. Gołebia 24, 31-007, Krakow, Poland

    Grzegorz Bryda

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  1. Grzegorz Bryda
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Correspondence to Grzegorz Bryda .

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Editors and Affiliations

  1. Department of Education and Psychology, Research Center on Didactics and Technology in Education of Trainers (CIDTFF), Ludomedia and University of Aveiro, Aveiro, Portugal

    António Pedro Costa

  2. Faculty of Engineering, Artificial Intelligence and Computer Science Laboratory (LIACC), University of Porto, Porto, Portugal

    Luís Paulo Reis

  3. Department of Education and Psychology, Research Center on Didactics and Technology in Education of Trainers (CIDTFF), University of Aveiro, Aveiro, Portugal

    António Moreira

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Bryda, G. (2020). From CAQDAS to Text Mining. The Domain Ontology as a Model of Knowledge Representation About Qualitative Research Practices. In: Costa, A., Reis, L., Moreira, A. (eds) Computer Supported Qualitative Research. WCQR 2019. Advances in Intelligent Systems and Computing, vol 1068. Springer, Cham. https://doi.org/10.1007/978-3-030-31787-4_6

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