Social Media as a Passive Sensor in Longitudinal Studies of Human Behavior and Wellbeing

Saha, K and Bayraktaroglu, A E and Campbell, A T. and Chawla, N V and Choudhury, D M and D'Mello, S K and Dey, A K and Gao, G and Gregg, J M and Jagannath, K and Mark, G and Martinez, G J and Mattingly, S M and Moskal, E and Sirigiri, A and Striegel, A and Yoo, D W (2019) Social Media as a Passive Sensor in Longitudinal Studies of Human Behavior and Wellbeing. In: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems.

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Social media serves as a platform to share thoughts and connect with others. The ubiquitous use of social media also enables researchers to study human behavior as the data can be collected in an inexpensive and unobtrusive way. Not only does social media provide a passive means to collect historical data at scale, it also functions as a "verbal" sensor, providing rich signals about an individual's social ecological context. This case study introduces an infrastructural framework to illustrate the feasibility of passively collecting social media data at scale in the context of an ongoing multimodal sensing study of workplace performance (N=757). We study our dataset in its relationship with demographic, personality, and wellbeing attributes of individuals. Importantly, as a means to study selection bias, we examine what characterizes individuals who choose to consent to social media data sharing vs. those who do not. Our work provides practical experiences and implications for research in the HCI field who seek to conduct similar longitudinal studies that harness the potential of social media data.

Item Type: Conference or Workshop Item (Paper)
Additional Information: The research paper was published by the author with the affiliation of Dartmouth College, Hanover
Subjects: Entrepreneurship
Date Deposited: 03 Apr 2021 10:44
Last Modified: 03 Apr 2021 11:06

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