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This course is an accessible introduction to the application of complexity theory to the social sciences, the course will be primarily focused upon the domain of sociology, but we will touch upon elements of psychology, anthropology, political science and economics. The aim of the course is to introduce you to the variety of models from complex systems and illustrate how they apply to these different domains. This course is a first of its kind and somewhat experimental in nature, where we will be drawing upon research from many different areas and using complexity theory to contextualize it into a coherent paradigm, giving us a fresh perspective with which to interpret some of the core questions within the social sciences.Content
The course is broken down into four main sections, in each section we will apply one of the major modelling frameworks from complexity theory to interpreting social phenomena. We will firstly give an overview to this area of social complexity before starting our first section on systems theory as we lay down a basic model of a social system, we will go on to use this model in helping us understand, social structure and institutions.
Next we will take an overview to nonlinear social science, as we discuss the process of self-organization, feedback loops, chaos theory and self-organized criticality. The third section to the course is dedicated to social network analysis, we will cover the main topics in this new area as we talk about the basics of social graphs, clustering, network structure and the process of diffusion. Finally we will be looking through the lens of complex adaptive systems theory, exploring the model of a fitness landscape, talking about adaptive capacity, social resilience and the process of evolution.
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Quick overview to the course
|Section 1: Social Systems Theory|
In this module we will be giving a quick overview to the application of complexity theory to the social sciences what we call social complexity, we start off with a very broad discussion surrounding the scientific enterprise as we talk about paradigms in general and the Newtonian paradigm in particular. We will go on to talk about how the basic assumptions underpinning our traditional formal approaches, begin to fail when we start to deal with more complex systems consisting of a very many autonomous, diverse, components, that are highly interconnected and interdependent, as often is the case within the social sciences.
In this video we continue on from our previous video as we briefly introduce complexity theory as an alternative approach to modeling these complex systems, an approach that is based upon a paradigm inherited from systems theory. Finally we touch upon how complexity science is based upon a new set of computational methods and how big data is set to have a transformative effect on the social sciences in the coming decades
|In this video we will be taking a very high-level view of what we mean by this term social system, we will be outlining our basic model as consisting of social actors called agents and a set of relations between them, we will talk about the idea of social agency and the different types of relations between these agents, finally we will discuss the types of social structures that emerge out of these relations and the dynamics of social systems as they change over time|
|Social institutions are a central object of study within the social sciences, they represent enduring patterns of organization or structures built up around some social function, religions, governments and families are all institutions that have stood the test of time because they provide essential structure and serve basic functions within social systems. In this video we will be talking about institutions through the lens of system theory talking about their efficiency, conflict theory and functionalism|
|In this video we will be talking about social structure and agency, we will look at how these two phenomena of agency and structure are deeply interdependent, with social structure emerging out of individuals giving over and combining their agency within organizations that both enable the individuals and constrain them. We will look at the different types of social structure and how they can be modeled in terms of the conditions under which the agents choose to join the organization|
|Section 2: Self-Organization & Nonlinearity|
In this video we will be talking about self-organization as a process of pattern formation within social systems, one that requires dense distributed peer-to-peer interactions within an unregulated environment in order to take hold. We talk about the nature of organization and how positive feedback loops are the key engines behind self-organization working to amplify some small event into a large systemic phenomena, creating local attractors that then have to cooperate or compete to get global coordination
|Feedback loops are central to the dynamics of nonlinear systems of all kind, from financial crisis, to population growth, to ecosystem collapse to the outbreak of conflict, they are the engines of self-organization. In this video we will be digging deeper into their workings as we talk about tipping points, thresholds path dependency and punctuated equilibrium|
In this module we will be talking about attractors and the fundamental role they play within social dynamics, both with respect to self-organization and chaos, we firstly give an outline to the model of a state space, we talk about how systems typically only occupy a small subset of the overall space as they cycle through some set of states. We will go on to discuss bifurcations and see how the process of continuous doubling in bifurcations is a universal feature of systems as they move into a chaotic and complex regime consisting of multiple attractors and equilibria
|In this video we will be looking at nonlinear social dynamics and self-organized criticality, as we talk about how positive and negative feedback can give us a model for interpreting these dynamics. We will briefly discuss how negative feedback can give us a relatively stable process of development involving counterbalancing forces that maintain the system within some equilibrium. We then go on to talk about a nonequilibrium process of change where this negative feedback loop gets broken and positive feedback coupled with negative externalities leads to rapid unsustainable development, within this dynamic, path-dependence, lock-in and heightened percolation all lead to eventual criticality and a phase transition|
|Section 3: Social Network Science|
|In this module we will be taking a very high level view to social network analysis, we talk about how connectivity creates a certain type of space, or what we call a topology that stretches and distorts our traditional conception of linear space. We discuss how reasoning about the general forces that are acting on the network can help us in providing some overall context to our analysis. We then go on to talk about some of the primary considerations to a social network's overall makeup and social cohesion, touching upon the topics of network density, clustering, average path length and degree distribution|
In this module we will be talking about social networks on the micro level, looking at agents and their local community. We will quickly talk about the basics of social graphs, before going on to discuss a number of different metrics for trying to understand how significant an agent is within a network, we will discuss interpersonal ties as we talk about strong and weak connections, finally we will look at the so-called small world phenomena
In this video we will been talking about three of the major factors shaping the overall make up to a social network, we start by talking about density of connections as a primary factor, next we will discuss average path length as a second key overall metric one that will tell us a lot about the network's overall cohesion. Lastly we look at degree distribution as playing an important role in defining the level of equality, the dynamics of power and how something will flow through the whole system
The study of network diffusion tries to capture the underlying mechanism of how events propagate through a complex network, whether the subject of interest is a virus spreading through some population, the spreading of some social movement, some new fashion or innovation or it may be a marketing message through an online social network. In this video we will be covering some of the primary considerations when looking at the process of diffusion including; how will the structure of the network effect that process? How fast will it spread, for example will we get tipping points? how can we enable or constrain this process?
|Section 4: Complex Social Systems|
In this module we will be looking through the lens of adaptive systems theory to see what insight it can offer us on macro social phenomena. Firstly we talk about adaptation as a process through which an agent tries to change its state in response to some change within its environment. We will give an outline to the adaptive landscape, that can be used as a formal model for representing whole complex social systems consisting of many interacting agents.
In this module we will be discussing adaptive capacity and resiliency within social systems. We talk about two different strategies for trying to manage change, resistance and adaptation. Where resistance involves developing, some static identity based upon a boundary condition and creating a regulatory system for monitoring and controlling the system's environment. Inversely we will then talk about adaptation as a second alternative strategy, one that is focused on the system's capacity to generate a wide set of responses, insuring its capacity to reconfigure itself given as wide a spectrum of input values as possible, in so doing ensuring its resilience and continued functionality. Finally we discuss the multidimensional nature to complex social systems being engaged in processes of change on various levels from the micro to the macro, giving us slow and fast variables
In this video we will be taking a brief overview to the process of evolution as it acts on macro scale socio-cultural systems. We describe evolution as a distributed process through which a complex adaptive system response to change within its environment without centralized coordination, and how through this process the system can develop over time to exhibit greater complexity. We will go on to talk about how evolution operates through a number of key strategies, that need to be performed successfully for the process to be effective
In this video we will be talking about institutions as performing social functions, we discuss a number of components to this process including the need for functional roles, some defined set of relations between these roles and their integration into some overall process that transforms an input to an output through a set of instructions either formal or informal. We will talk about how institutions may be dysfunctional, leading to the generation of social entropy a state of disintegration and decay that needs to be exported in some fashion from the social system in order to maintain its structure and functionality, finally we talk about the differences between formal and informal institutions
Think Academy is an e-Learning site dedicated to the area of systems thinking and complexity theory, our mission is to take the world of complexity and make it accessible to all. Systems and complex can be intimidating subjects with many sophisticated concepts, this is why we believe it is important to always start with the most essential, simplest elements of a subject making sure that students come away with a solid understanding of the core concepts behind each area. As Einstein said "Make everything as simple as possible, but not simpler"
Courses are curated and presented by Joss Colchester. Joss has extensive experience within the domain of complex systems both within academic research(mathematical modeling of complex system + network analysis) and has many years practical systems engineering experience(designing and developing complex web based information systems). He has a passion for taking abstract and complex concepts and making them concrete and accessible to as broad an audience as possible by combining clear and effective graphics with well structured course content.