Social network analysis of the mental health sub-topic on the MedlinePlus subject directory

Author:

Zhu Yifan, ,Zhang Jin,

Abstract

Introduction. A subject directory plays an important role in a Web portal and it helps users effectively navigate the portal. This study examines a subject directory system related to Mental Health in the MedlinePlus portal and provides suggestions of optimisation to enhance the subject directory system. Method. A mixed research method combining social network analysis and inferential statistics was applied. Analysis. A structural and a semantic social network were built regarding the selected health topics related to mental health in the MedlinePlus portal. The two networks were compared and the outcomes were evaluated by domain experts. Results. Among the ninety-nine collected health topics related to mental health, three themes were identified through the visualisation analysis regarding grouped health topics. Patterns and characteristics of each theme group were discussed. As a result, fifty-five bidirectional and twenty-three unidirectional edges were identified and recommended to be added to the corresponding health topic pages. The recommended results indicate that the subject directory of specific mental health related topics is well constructed, while health consumer groups related topics might need more improvements. The optimised subject directory has significantly stronger semantic connection, and the results of the recommendations are consistent with the evaluation outcome of two domain experts. Conclusions. The findings of this study can provide ideas of optimising and enhancing the subject directory system to the public health portal creators and health professionals, and benefit health consumers for seeking health information online. The methodologies applied in this study may provide a novel way to investigate and enhance subject directories in general.

Publisher

University of Boras, Faculty of Librarianship, Information, Education and IT

Subject

Library and Information Sciences

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