This page is simply to publicize some of my coding experience and material. You can find more material in my GitHub profile: https://github.com/IgnacioOQ
Data Science Specialization Certification (10 courses by Johns Hopkins University - R)
Reinforcement Learning Specialization Certification (4 courses by University of Alberta - Python)
Deep Learning with Tensorflow Certification (4 courses by DeepLearning.AI - Python), Natural Language Processing with Tensorflow Certification (1 course by DeepLearning.AI - Python).
Social and Economic Networks Certification (1 course by Stanford University), Network Dynamics and Social Behavior Certification (1 course by University of Pennsylavia - Netlogo), Advanced Game Theory Applications Certification (1 course by Stanford University)
"Attention and counter-framing in the Black Lives Matter movement on Twitter" Respository.
"Polarization and trust in the evolution of vaccine discourse on Twitter during Covid-19"Repository.
Netlogo Network Segregation This model allows you to simulate homophilic and heterophilic dynamics in directed and undirected Erdős–Rényi random networks. If agents find that their "friends" do not satisfy their homophilic or heterophilic preferences, then they cut ties and find new friends. The upshot is to observe how segregation may emerge under minor homophilic preferences, as well as to observe the interaction between homophily and heterophily.
Contagion diffusion on Networks This model generates Erdős–Rényi random networks, as well as Barabási–Albert Preferential Attachment networks. On that, you are allowed to impose a SIR Epidemiological model in order to study the effect of contagion over different networks.
Empathy and Compassion Does Love trump Hate? This short model attempts to provide an answer to the guiding question by providing a very simple model for human interaction among different groups, and for empathic reactions and adjustments. The upshot is to study the conditions in which a population with different groups of people may overcome antipathy given some starting conditions. The model, although very simplistic, has the advantage of being very simple. This model has two groups, interacting and this one has four. Read the description for elaboration.
Bias and information exchange in scientific inquiry This model studies the effect of information sharing when agents are biased, and it shows that given a set of biased agents, information sharing washes the biases out. Read the description for more information.
Reference coalitions and academic isolation The purpose of this model is to study the strategic dimensions of one way of assigning reputation in academic contexts: references. See the description for more details.
Please visit my GitHub for some of my projects involving Data Science.