Creativity, Innovation, Participation, Collaboration
Down Networks is a real time, progressively agile non profit startup whose goals are to fund its research via pragmatically aggressive altruistic entrepreneurial pursuits informed by proprietary in-house techniques, open source technology and refined scientific methodology.
Agent-based Modeling, Maching Learning, Algorithmic Marketing, Diffusion of Innovations, Online Communities
structure of scientific revolutions, dynamics of innovation, exploration-exploitation dynamics
I’m a PhD researcher at the University of Glasgow working on modelling political polarisation on social media platforms suing agent-based models
agent-based models, social networks, python, R, NetLogo
My research aims to explore the potential of network science for the archaeological discipline. In my review work I confront the use of network-based methods in the archaeological discipline with their use in other disciplines, especially sociology and physics. In my archaeological work I aim to develop and apply network science techniques that show particular potential for archaeology. This is done through a number of archaeological case-studies: archaeological citation networks, visibility networks in Iron Age and Roman southern Spain, and tableware distribution in the Roman Eastern Mediterranean.
PhD student in The Robert Zajonc Institute for Social Studies at the University of Warsaw.
network science; social networks; sociology; complex systems; ecological psychology; cognitive science; perception and action
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
PhD student at University of Toronto: memes, social networks, contagion, agent based modeling, synthetic populations