کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
515392 867007 2013 30 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A user term visualization analysis based on a social question and answer log
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
A user term visualization analysis based on a social question and answer log
چکیده انگلیسی


• A user-based diabetes subject directory was discovered in this study.
• Terms and their relationships in each of the 12 categories were visually displayed and analyzed.
• The relationships among the 12 categories were analyzed in a visual context.
• Descriptive statistic data on diabetes in the Q&A were revealed.

The authors of this paper investigate terms of consumers’ diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers’ perspective, and reveal users’ diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing & Management - Volume 49, Issue 5, September 2013, Pages 1019–1048
نویسندگان
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