Measuring the Health and Well-Being of Populations through Social Media
Johannes Eichstaedt, PhD candidate, , University of Pennsylvania
The expression of millions of users on social media is one of the largest longitudinal and cross-sectional data collection efforts in human history, with great potential for psychology and public health. Penn has become a hub for this research in the US. By applying computational language analysis to Facebook, we can better understand personality and track emotional experience over time; by analyzing Twitter, we can predict geographical variation in heart disease and well-being, and identify its psychological correlates at the community level. Research highlights will be shared from in this four year project.
I am a data scientist in psychology. I use Facebook and Twitter to measure the psychological states of large populations, and even small populations. We are characterizing the psychological profiles of communities that support their well-being, or make them sick.
I’m a PhD student in psychology at the University of Pennsylvania under Martin Seligman. In 2011 I co-founded the World Well-Being Project, a team that uses clever Natural Language Processing and machine learning to, well, measure the well-being of the world. Eventually.
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