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• W2904137377 abstract "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." @default.
• W2904137377 created "2018-12-22" @default.
• W2904137377 creator A5009018290 @default.
• W2904137377 creator A5010380816 @default.
• W2904137377 date "2018-12-08" @default.
• W2904137377 modified "2023-09-23" @default.
• W2904137377 title "An Exploratory Study of (#)Exercise in the Twittersphere" @default.
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