Integrated entitymetrics analysis for health information on bipolar disorder using social media data and scientific literature
Aslib Journal of Information Management
ISSN: 2050-3806
Article publication date: 22 August 2022
Issue publication date: 19 June 2023
Abstract
Purpose
This study aimed to examine the mental health information entities and associations between the biomedical, psychological and social domains of bipolar disorder (BD) by analyzing social media data and scientific literature.
Design/methodology/approach
Reddit posts and full-text papers from PubMed Central (PMC) were collected. The text analysis was used to create a psychological dictionary. The text mining tools were applied to extract BD entities and their relationships in the datasets using a dictionary- and rule-based approach. Lastly, social network analysis and visualization were employed to view the associations.
Findings
Mental health information on the drug side effects entity was detected frequently in both datasets. In the affective category, the most frequent entities were “depressed” and “severe” in the social media and PMC data, respectively. The social and personal concerns entities that related to friends, family, self-attitude and economy were found repeatedly in the Reddit data. The relationships between the biomedical and psychological processes, “afraid” and “Lithium” and “schizophrenia” and “suicidal,” were identified often in the social media and PMC data, respectively.
Originality/value
Mental health information has been increasingly sought-after, and BD is a mental illness with complicated factors in the clinical picture. This paper has made an original contribution to comprehending the biological, psychological and social factors of BD. Importantly, these results have highlighted the benefit of mental health informatics that can be analyzed in the laboratory and social media domains.
Keywords
Acknowledgements
Funding: This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A5B1104865).
Citation
Timakum, T., Song, M. and Kim, G. (2023), "Integrated entitymetrics analysis for health information on bipolar disorder using social media data and scientific literature", Aslib Journal of Information Management, Vol. 75 No. 3, pp. 535-560. https://doi.org/10.1108/AJIM-02-2022-0090
Publisher
:Emerald Publishing Limited
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