An exploratory study of (#)exercise in the Twittersphere

Karami, Amir; Shaw, George

Permalink

https://hdl.handle.net/2142/103327 Copy

Description

Title

An exploratory study of (#)exercise in the Twittersphere

Author(s)

• Karami, Amir
• Shaw, George

Issue Date

2019-03-15

Keyword(s)

• Twitter
• Text mining
• Topic modeling
• Health informatics
• Exercise

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 an effective approach to summarizing the various characteristics of text data for different health and medical applications.

Publisher

iSchools

Series/Report Name or Number

iConference 2019 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/103327

DOI

https://doi.org/10.21900/iconf.2019.103327

Copyright and License Information

Copyright 2019 Amir Karami and George Shaw

Owning Collections