Tuesday, May 26, 2020 | 10:00 am | Zoom

Title: Mathematical Study of Human Dynamics with Modeling of Collective Motion and Social Media

Abstract

We present three projects with the underlying theme of human dynamics. In this work, we especially focus on the collective behavior and communication aspects of human dynamics. First, we mimic a real-life evacuation using the Social Force model. The Social Force model is a seminal model for the collective dynamics of pedestrian crowds, and it has been widely applied. We evaluate the Social Force model by comparing the results with experimental data. We find that changing the model’s interaction parameters is essential when fitting the model to the experimental data, indicating that a more nuanced application of the social force model might be necessary in evacuation scenarios. Following the theme of collective behavior, we next perform numerical experiments to explore the open question of whether it is possible to obtain the same behavior from a particle model as the number of particles changes, by scaling the parameters, as proposed by Barbaro et al. in 2009. We focus on the Vicsek model with and without repulsion. We find that scaling does not necessarily preserve the same behavior. Lastly, we examine the communication aspect of human dynamics through social media. We work with Twitter data from the 2015 Baltimore protests to build a tool, using quantiles and Nonnegative Matrix Factorization, that shows promise for predicting civil unrest in real-time. In addition to introducing the tool, we provide thorough explanations of background on the event, the data cleaning process, and the data itself.

Advisor: Dr. Alethea Barbaro

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