An Exploratory Study of (#)Exercise in the Twittersphere
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 an effective approach to summarizing the various characteristics of text data for different health and medical applications.
Digital Object Identifier (DOI)
iConference 2019 Proceedings, 2019.
© Amir Karami and George Shaw, 2019
Shaw, G. Jr, Karami, A. (2019). An Exploratory study of (#)exercise in the Twittersphere. Proceedings of the iConference, Washington, DC.