Thursday, October 31, 2019

Talk: Utilizing Agent-based Models and Open Data to Examine the Movement of People and Information

Earlier this month I was invited to give a talk as part the Criminal Investigations and Network Analysis Center (CINA) Distinguished Speaker Series. As readers of the blog might expect, I chose to talk about how open data (e.g. OpenStreetMap, Twitter) can be utilized in agent-based models to study a variety of applications (many of which can be found over on my research page). The talk itself was entitled: "Utilizing Agent-based Models and Open Data to Examine the Movement of People and Information: A Gallery of Applications." Below you can read the brief abstract of the paper and if this peaks your interest, CINA recorded my talk and highlighted (short) version  is given below (while the full talk can be found at: https://youtu.be/iIvSnE-IBZI).

Abstract: 
Today we are awash with many new forms of open data (e.g. crowdsourced, social media), but we are still challenged with how individuals make decisions and how this leads to more aggregate patterns emerging. One way to explore how individuals make decisions, or are impacted by information and their resulting consequences, is via agent-based modeling. Agent-based modeling allows for simulating heterogenous actors and their decision-making processes within complex systems. Through a series of example applications ranging from the small-scale movement of pedestrians over seconds, to that of the movement of people over borders over hours and days, I will demonstrate how open data can be leveraged within the agent-based building process. Specifically, the examples will show that by focusing on individuals, or groups of individuals and the networks that connect them, more aggregate patterns emerge from the bottom up.


Friday, October 25, 2019

Papers at CSSSA Conferece

At the  2019 Computational Social Science Society of Americas (CSSSA) Conference, we have two papers being presented which relates to our interests in urban simulation. Full citations and links to them are provided at the bottom of this post, while what follows provides a brief overview to them. Turning first to the the paper entitled "Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach," co-authored with Niloofar Bagheri-Jebelli and Bill Kennedy explores how agents choices for specific locations within a city leads to gentrification occurring. The  model and data that accompanies the paper can be found at: https://github.com/niloofar-jebelli/UrbanDynamics, while below we provide the abstract of the paper, the graphical user interface of the model along with movie of one simulation run with default model settings.

Abstract:
Cities are complex systems which are constantly changing because of the interactions between the people and their environment. Such systems often go through several life cycles which are shaped by various processes. These may include urban growth, sprawl, shrinkage, and gentrification. These processes affect the urban land markets which in turn affect the formation of a city through feedback loops. Through models we can explore such dynamics, populations, and the environments in which people inhabit. The model proposed in this paper intends to simulate the aforementioned dynamics to capture the effect of agents’ choices and actions on the city structure. Specifically, this model explores the effect of gentrification on population density and housing values. The proposed model is significant in its integration of ideas from complex systems theory which is operationalized within an agent-based model stylized on urban theories to study gentrification as a cause of increased in land values. The model is stylized on urban theories and results from the model show that the agents move to and reside in properties within their income range, neighboring agents that have similar economic status. The model also shows the role of gentrification by capturing both the supply and demand aspects of this process in the displacement and immobilization of agents with lower incomes. This is one of the first models that combines several processes to explore the life cycle of a city through agent-based modeling.

Keywords: Urban Dynamics, Land Markets, Gentrification, Urban Growth, Urban Shrinkage, Urban Sprawl.

Model graphical user interface at default settings.


Gentrification by demand in the 10th neighborhood of the inner-city.

Turning to our second paper which was presented as a poster, entitled "Modeling Social Networks in an Agent-Based Model of a Nuclear Weapon of Mass Destruction Event" we discussed our continuing  work on disasters. Specifically our project on how people might react in an event of  Nuclear Weapon of Mass Destruction (NWMD) in New York City when one integrates social networks into an agent-based model. In the paper we discuss preliminary results which demonstrate how we can integrate  household social networks explicitly into a spatially explicit model. Furthermore we demonstrate and benchmark agent commuting patterns for the New York City Commuter Region with a sample population  (as we show in one of the movies below) along with demonstrating agents initial reactions post NWMD detonation.

Abstract:
Connections between human beings often influence where people go and how they behave, yet their representation as social networks are rarely modeled as a factor of human behavior in agent-based models. Social networks are increasingly being used to study human behavior in disasters, and empirical work has shown that human beings prioritize the safety of themselves and loved ones (i.e., households) before helping neighbors and coworkers. In this poster, we briefly present our agent-based model being used to characterize the New York City area population’s reaction to a Nuclear Weapon of Mass Destruction (NWMD) event. The model methodology demonstrates how social networks can be integrated into an agent-based model and act as a basis for decision-making during a disaster. Preliminary simulations show how agents potentially respond to a NWMD event with measurable changes in location and network formations over space and time.
Keywords: Agent-Based Model, Human Behavior, Social Networks, Emergency, Disaster Response, Nuclear Weapon of Mass Destruction.







References
Bagheri-Jebelli, N., Crooks, A.T. and Kennedy, W.G. (2019), Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach, The 2019 Computational Social Science Society of Americas Conference, Santa Fe, NM. (pdf)

Burger, A. G., Kennedy, W.G., Crooks, A.T., Jiang, N. and Guillen-Piazza, D. (2019), Modeling Social Networks in an Agent-Based Model of a Nuclear Weapon of Mass Destruction Event, The 2019 Computational Social Science Society of Americas Conference, Santa Fe, NM. (paper pdf) (poster pdf)