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arXiv 1812.03260stat.APcs.CLcs.CYstat.ML
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An Exploratory Study of (#)Exercise in the Twittersphere

University of North Carolina at Charlotte(北卡罗来纳大学夏洛特分校);University of South Carolina(南卡罗来纳大学)

George Shaw, Amir Karami

英文摘要:

Social media analytics allows us to extract, analyze, and establish semantic from user-generated contents in social media platforms. This study utilized a mixed method including a three-step process of data collection, topic modeling, and data annotation for recognizing exercise related patterns. Based on the findings, 86% of the detected topics were identified as meaningful topics after conducting the data annotation process. The most discussed exercise-related topics were physical activity (18.7%), lifestyle behaviors (6.6%), and dieting (4%). The results from our experiment indicate that the exploratory data analysis is a practical approach to summarizing the various characteristics of text data for different health and medical applications.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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