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

机译:社交媒体作为一种被动传感器,在人类行为和福祉的纵向研究中

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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.
机译:社交媒体作为分享思想和与他人联系的平台。无处不在的社交媒体使用也使研究人员能够研究人类行为,因为数据可以以廉价且不起的方式收集。社交媒体不仅提供了以规模收集历史数据的被动手段,它还用作“口头”传感器,为个人的社会生态背景提供丰富的信号。本案例研究介绍了基础设施框架,以说明在工作场所性能的持续多模式传感研究的上下文中被动地收集社交媒体数据的可行性(n = 757)。我们与个人的人口统计,人格和福祉属性的关系讨论了我们的数据集。重要的是,作为学习选择偏见的手段,我们检查选择同意社交媒体数据共享与那些没有的人的特征。我们的工作为寻求进行类似纵向研究的HCI领域的研究提供了实际的经验和影响,这些研究是利用社交媒体数据的潜力的相似纵向研究。

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