Interactive content analysis : evaluating interactive variants of non-negative Matrix Factorisation and Latent Dirichlet Allocation as qualitative content analysis aids
Bakharia, Aneesha (2014) Interactive content analysis : evaluating interactive variants of non-negative Matrix Factorisation and Latent Dirichlet Allocation as qualitative content analysis aids. PhD thesis, Queensland University of Technology.
This thesis addressed issues that have prevented qualitative researchers from using thematic discovery algorithms. The central hypothesis evaluated whether allowing qualitative researchers to interact with thematic discovery algorithms and incorporate domain knowledge improved their ability to address research questions and trust the derived themes. Non-negative Matrix Factorisation and Latent Dirichlet Allocation find latent themes within document collections but these algorithms are rarely used, because qualitative researchers do not trust and cannot interact with the themes that are automatically generated. The research determined the types of interactivity that qualitative researchers require and then evaluated interactive algorithms that matched these requirements. Theoretical contributions included the articulation of design guidelines for interactive thematic discovery algorithms, the development of an Evaluation Model and a Conceptual Framework for Interactive Content Analysis.
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|Item Type:||QUT Thesis (PhD)|
|Supervisor:||Bruza, Peter, Sitbon, Laurianne, Watters, Jim, & Lakshminarayanan, Bhuva|
|Keywords:||Qualitative Content Analysis, Computer-Aided Content Analysis, Inductive Content Analysis, Conventional Content Analysis, Thematic Analysis, Topic Modelling, Text Analysis, Non-negative Matrix Factorisation, Latent Dirichlet Allocation|
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Institution:||Queensland University of Technology|
|Deposited On:||29 Oct 2014 05:48|
|Last Modified:||03 Sep 2015 05:05|
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