alexa Content analysis of cancer blog posts.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Kim S

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Abstract OBJECTIVES: The efficacy of user-defined subject tagging and software-generated subject tagging for describing and organizing cancer blog contents was explored. METHODS: The Technorati search engine was used to search the blogosphere for cancer blog postings generated during a two-month period. Postings were mined for relevant subject concepts, and blogger-defined tags and Text Analysis Portal for Research (TAPoR) software-defined tags were generated for each message. Descriptive data were collected, and the blogger-defined tags were compared with software-generated tags. Three standard vocabularies (Opinion Templates, Basic Resource, and Medical Subject Headings [MeSH] Resource) were used to assign subject terms to the blogs, with results compared for efficacy in information retrieval. RESULTS: Descriptive data showed that most of the studied cancer blogs (80\%) contained fewer than 500 words each. The numbers of blogger-defined tags per posting (M = 4.49 per posting) were significantly smaller than the TAPoR keywords (M = 23.55 per posting). Both blogger-defined subject tags and software-generated subject tags were often overly broad or overly narrow in focus, producing less than effective search results for those seeking to extract information from cancer blogs. CONCLUSIONS: Additional exploration into methods for systematically organizing cancer blog postings is necessary if blogs are to become stable and efficacious information resources for cancer patients, friends, families, or providers.
This article was published in J Med Libr Assoc and referenced in Journal of Proteomics & Bioinformatics

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