Niloofar Bagheri Jebelli

Niloofar Bagheri Jebelli

Computational Social Scientist

Posts by Collection

projects

publications

Modeling the Impact of Fake News on Citizens

Published in International Conference on Cognitive Modelling, 2018

We built a cognitive model of a citizen deciding what to believe when encountering election stories on social media, eventually developing an opinion and using motivated reasoning to help determine which stories are true.

Recommended citation: Tulk, S., Bagheri Jebelli, N., Kennedy, W. G., “Modeling the Impact of Fake News on Citizens”. Proceedings of the 16th Annual Meeting of the International Conference on Cognitive Modelling (pp. 187-192), Madison, USA: University of Wisconsin, 2018. http://niloofar-jebelli.github.io/files/ICCM-2018-Modeling-the-Impact-of-Fake-News-on-Citizens.pdf

Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach

Published in The Computational Social Science Society of Americas Conference, 2019

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.

Recommended citation: Bagheri-Jebelli, N., Crooks, A.T. and Kennedy, W.G., “Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach”, The Computational Social Science Society of Americas Conference, Santa Fe, NM, USA, 2019. http://niloofar-jebelli.github.io/files/CSSSA-2019-Gentrification_Property-Values.pdf

Social Network Analysis of Gobekli Tepe: Belief Propagation in 10th Millennium BC

Published in International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, 2020

Utilizing agent-based modeling and social network analysis tools, this paper investigates the belief propagation to observe the emergence of leaders among the population and examines the network structure of the communities constructing Gobekli Tepe.

Recommended citation: Bagheri-Jebelli, N., Kennedy, W.G., “Social Network Analysis of Gobekli Tepe: Belief Propagation in 10th Millennium BC”, International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, Washington, D.C., USA, 2020. http://niloofar-jebelli.github.io/files/SBP_BRiMS_2020_GT_SNA_NBJ_WK.pdf

talks

Urban Development Through the Lens of Agent-based Modeling

Published:

Cities are ever changing and growing phenomenon with many underlying complexities. Through its life cycle, a city experiences various forms of dynamics. Models allow for a better understanding of such complexities and dynamics. The model developed in this thesis intends to simulate the dynamics of certain processes such as: an urban market, agent interactions in that market, urban growth, sprawl and shrinkage and gentrification. The purpose of this model is to understand the behavioral pattern of the agents and demonstrate the life cycle of a city based on individual agents’ actions. This model is significant in its integration of various subsystems creating a larger system while observing developers’ behavior. Specifically, the model explores some well-known issues, including the Smith’s rent-gap theory, Burgess’s concentric zones model of urban growth, and Alonso’s bid rent theory. The main results from the model show that the agents move to and reside in properties within their income range, with similar neighbors. This is one of the first models that provides a new lens to explore urban development.

A Computational Approach to Initial Social Complexity: Gobekli Tepe and Neolithic Polities in Urfa Region, Upper Mesopotamia, Tenth Millennium BC

Published:

Extensive archaeological field work and multidisciplinary research in recent decades shows that communities of sedentary hunter-gatherers during the tenth millenium BC built the earliest presently known monumental structures during the PPNA (ca. 9600–8800 BC) at the site of Göbekli Tepe and nearby PPNB sites in present-day Urfa province, southeastern Turkey. However, the earliest evidence of agriculture began further south (e.g., the Levant) or dates to a later period (early PPNB, ca. 8750 BC, terminus post quem). We present a novel computational analysis of initial social complexity in these early Anatolian communities, based on Canonical Theory of politogenesis, evolutionary dynamics, and lines of evidence drawn from published data on Göbekli Tepe and related Urfa sites. Theory and data are then used to create an agent-based model simulating the emergence of worship sites, other diffused cultural patterns, and the emergence of cultivation as may have occurred in the region during the PPNA and initial PPNB periods. The model is implemented in NetLogo. Along with other computational models of early social complexity, it aims to contribute to multidisciplinary understanding of prehistory, origins of civilization, and long-term culture change. Extensions of the model to other regions of politogenesis are also discussed.

Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach

Published:

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.

Social Network Analysis of Gobekli Tepe: Belief Propagation in 10th Millennium BC

Published:

For years, we believed that the transition of human communities from simple hunter-gatherer societies to complex sedentary societies occurred due to the expansion of cultivation and the rise of agriculture. Gobekli Tepe, a pre-pottery Neolithic site in Turkey, presents a new explanation that can shed light on the human development to civilization. This archaeological site was constructed through the collaboration of various hunter-gatherer societies as a communal space for ritualistic purposes. Studies show a similarity in architecture, tools, crops and symbolism of some of Gobekli Tepe’s neighboring cultures. The commonalities suggest the existence of a shared belief before the construction of the site. Utilizing agent-based modeling and social network analysis tools, this paper investigates the belief propagation to observe the emergence of leaders among the population and examines the network structure of the communities constructing Gobekli Tepe. Most importantly, this site represents a complex adaptive system where the interactions of its components may have caused the emergence of a belief institution.

Computational Modeling of the Social Complexity in Göbekli Tepe and Earliest Neolithic Communities

Published:

For years, we believed that the transformation of human communities from simple nomadic hunter-gatherer societies to complex sedentary societies occurred due to the expansion of cultivation and the rise of agriculture. Accepting this perspective as premise to years of archaeological research limited the field in investigating alternative explanations to the significant socio-cultural transition which potentially led to years of collaborative efforts in the Mesopotamian region of West Asia. Göbekli Tepe, a pre-pottery Neolithic site in Turkey, requires such alternative explanations for the Neolithic Revolution. Since the site was discovered, various excavations and analyses have been conducted. However, all such investigations include traditional archaeological methods and expectations. This research proposes a multidisciplinary theory of the development of the social complexity of Göbekli Tepe and the contemporary communities in the Urfa region prior to the rise of agriculture. Understanding the interplay of factors resulting in group identity and social cohesion shed light on the reasons that motivated the collective action of hunter-gatherer societies of the region to construct this communal space for ritualistic purposes. This research, rooted in complex system theory, pioneers a novel exploration of the nonlinear dynamics of humanhuman and human-environment interactions among Neolithic communities. Utilizing a multi-method computational approach, it delves into group identity and social cohesion, departing from prior studies confined to single quantitative methods. The study employs quantitative and qualitative socio-cultural and environmental data to construct an artificial society, unveiling nuanced factors shaping interactions. Through agent-based modeling and social network analysis, it sheds light on the dynamics of trust, cooperation, leadership emergence, belief propagation, and universal narratives, offering insights into historical and contemporary societal behaviors.

teaching

CDS 101: Introduction to Computational and Data Sciences

Undergraduate course, George Mason University, Computational Social Science Department, 2019

Course Description: During this course, students will develop basic skills for obtaining, cleaning, transforming, and visualizing real-world datasets using the R programming language and the RStudio integrated development environment. Statistical methods for analyzing, interpreting, and predicting dataset trends are then introduced and approached from a computational point of view using randomization and simulation. Additional topics may be covered, such as an introduction to advanced or special topics like cross-validation. Throughout the course emphasis is placed on documenting one’s scientific work using RStudio in conjunction with Github to fulfill the principles of reproducible research. Connections are highlighted between statistical inference and the scientific method and how this is related to both the scientific method’s power and its limitations. These tools will also be used to critically examine statistical claims reported in mass media, demonstrating how scientific literacy and a basic knowledge in statistics are indispensable tools to making sense of our modern world.