SIG DSA - Data Science and Analytics for Decision Support
Loading...
Paper Type
Complete
Paper Number
1245
Description
mHealth technologies seek to improve personal wellness; however, there are still significant privacy and security challenges. The purpose of this study is to analyze tweets through social media mining to understand user-reported concerns associated with mHealth devices. Triangulation was conducted on a representative sample to confirm the results of the topic modeling using manual coding. The results of the emotion analysis showed 67% of the posts were largely associated with anger and fear, while 71% revealed an overall negative sentiment. The findings demonstrate the viability of leveraging computational techniques to understand the social phenomenon in question and confirm concerns such as accessibility of data, lack of data protection, surveillance, misuse of data, and unclear policies. Further, the results extend existing findings by highlighting critical concerns such as users’ distrust of these mHealth hosting companies and the inherent lack of data control.
Recommended Citation
Mitchell, Damion R. and El-Gayar, Omar, "Privacy and Security Concerns Associated with mHealth Technologies: A Computational Social Science Approach" (2022). AMCIS 2022 Proceedings. 8.
https://aisel.aisnet.org/amcis2022/sig_dsa/sig_dsa/8
Privacy and Security Concerns Associated with mHealth Technologies: A Computational Social Science Approach
mHealth technologies seek to improve personal wellness; however, there are still significant privacy and security challenges. The purpose of this study is to analyze tweets through social media mining to understand user-reported concerns associated with mHealth devices. Triangulation was conducted on a representative sample to confirm the results of the topic modeling using manual coding. The results of the emotion analysis showed 67% of the posts were largely associated with anger and fear, while 71% revealed an overall negative sentiment. The findings demonstrate the viability of leveraging computational techniques to understand the social phenomenon in question and confirm concerns such as accessibility of data, lack of data protection, surveillance, misuse of data, and unclear policies. Further, the results extend existing findings by highlighting critical concerns such as users’ distrust of these mHealth hosting companies and the inherent lack of data control.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIG DSA