Online Human Behavior and Power Law Network - Assignment Example

Question A. According to Joshi (1999), online human behavior especially in relation to social networks can be explained using four clusters i.e. degree of separation, clustering, small world networks and robustness. The social networks are structured in a way that there are relationships between social entities. These entities include organizations, groups of people and websites. In terms of robustness, these social networks are analyzed using the percolation theory. If a link is removed from a network, it becomes segmented in to small disconnected segments called clusters. Therefore, the way user access and interact on social media in these small robust networks helps in understanding the behavior of human beings. In reference to the degree of separation, everyone in the social network are separated and are at fewer steps away and interact through introduction form another person and the chain continues. Therefore, how these separated people interact, the kind of connections they make and to whom, what thy share and how they relate online will help in understanding the human behavior on social media. B. The power law network is a network whose distribution follows the power law asymptotically. The power law is a relationship between two quantities where one variable is varies as the power of another. Examples of these networks include the World Wide Web links, social networks or biological networks. Power law networks have a characteristic of clustering. This will therefore help organizations like Amazon know how well their nodes and their customers are interconnected within a specified area of the network. It will help the company know how many of a person’s friends also know each other and how this may influence their shopping culture. (Jackson, 2000) C. Power law networks can be subject to two different attacks i.e. random and international attacks. Power law networks are less robust as compared to scale-free network hence making them vulnerable for attacks. Therefore, the vulnerability under random attacks is enhanced by lack of robustness control in such networks. Also, the failures are in these networks are facilitated by large scale cascades coupled with an increase in driver nodes. This is because the number of nodes is related to the amount of edges in the connecting components hence the vulnerability to attacks. (Jackson, 2000) Question 2 A. Complex systems exhibit several characteristics (Jackson, 2000). They include: Feedback loops. In this case, it refers to a change in variable results either positively or negatively. A part of a system receives feedback when the way its neighbors interact with it at a later time depends on how it interacts with them at an earlier time. Complex systems have many interdependent variables hence making it difficult to pin out which input contributes to a particular output and the extent of each variable’s contribution to the output. They are characterized by chaotic behavior i.e. they are extremely sensitive to change of initial conditions, fractal geometry and self-organized criticality. They exhibit non-Gaussian distribution of outputs. This implies that the events that are unlikely are less likely. This means that events whose outcomes are far away from average are more likely than they would be in a Gaussian distribution. Complex systems are also characterized by multiple meta-stable states where any changes in a system lead to change in a whole system. Complex systems are non-linear. This means that any addition of two solutions or multiplication of the solutions does not lead to another solution. Therefore, the superposition principle does not apply in complex systems. B. These feature manifest themselves during systems development in the following ways (Jackson, 2000): Feedback Loops: This characteristic manifests itself during systems development when a system to be developed uses a feedback mechanism in order to function. For instance, in the development of a thermostat, the feedback will be important in regulating the temperature of a place. Non-Gaussian distribution of outputs: Most systems developers have the ability to predict future systems behaviors based on data collected over a short period of time. This characteristic of systems is done using the Gaussian estimates during systems development. Multiple meta-stable states: This manifests itself during systems development when small changes are made to a system. Altering a certain logical procedure may affect the whole functionality of a system. Chaotic behavior: This comes out clearly when a change is made into initial conditions of the system during development. This small change may result in a totally different outcome hence the chaotic behavior. Interdependent variables: During systems development, it may be difficult to know which input variables actually contribute to a certain output. This is because the variable are strongly dependent. Question 3 The fitness landscape can be represented as N-dimensional terrain, where the height of the landscape represents the organisms fitness and this analogy can be used to explain the complexity theory. K here represents the extent to which the contribution of one gene to fitness depends on other genes. The higher K, the more genes interact and constrain each other, with the result that the fitness landscape is more rugged with more local peaks. Organisms can move across this landscape, searching for higher levels of fitness, through processes of mutation and natural selection. An organism might mutate one gene at a time, at random, and test whether it helps it climb the landscape. Both of these processes lead organisms to climb local peaks, and natural selection then favors those at more distant higher peaks. This search process is aided by two important features of fitness landscapes with a moderate amount of ruggedness. High peaks are associated with large basins of attraction, just as high mountains tend to cover large geographic areas. As a result, if a population starts off randomly distributed over the landscape, more organisms will end up on higher peaks than on lower ones. (Bak, Tang & Wiesenfeld, 1998) A rugged landscape gives rise to a diversity of organizational forms, whereas the rules of natural selection helps one form to be dominant. This approach integrates adaptation at the organizational level with the population ecology view as mechanisms for generating fit between organizations and their environments. The tendency to become stuck on local fitness peaks suggests the importance of path dependency, since most organizations are always in search for the highest peaks on a landscape. Also, for tightly coupled systems, in which each characteristic of the firm is related to many others, they find it harder to adjust to changes in their environment. This is because their landscapes are too rugged with many local peaks, so that local search provides little information concerning the location of more distant but higher fitness terrain. (Conejero, 2010) The concept of landscapes make it hard for companies to adapt technological change that affects the architecture of systems, meaning the basic structural configuration of components. When the system is tightly coupled technologically, a change to any one component may require changes in the others and in the way the entire system is configured. Forecasting is particularly difficult in systems that never approach a stable equilibrium state. Question 4 A. An externality normally arises when a third party to a transaction experiences side effects which can be negative or positive to them. In case a third party benefits from the transaction, it leads to a positive externality while if they suffer a loss a negative externality occurs. In a social media perspective, externalities occur when there are more and more people joining the online social media sites hence leading to s trend where more people are joining without assessing its value. This is the positive externality. Negative externality can also occur where more user make social media less valuable due to more people joining hence increasing in congestion. Within time, the positive externalities leads to a bandwagon as the network becomes more valuable and more people join in that positive feedback loop. (Joshi, 1999) C. Supervenience is an ontological relation that is applied in describing the lower level properties of a system in order to determine its higher level properties. It is argued by philosophers that a world is made up of a hierarchy of properties where the lower properties are supervened by higher level properties. Emergent properties arise from fundamental entities and are normally irreducible in respect to these entities. An emergent property refers to a property contained by complex systems. A property is said to be emergent when it is supervened by a higher property. (Joshi, 1999) Question 5 A. Conway’s way of life is a game that is an implementation of cellular automata. It stimulates death and birth of certain organisms based on certain rules. The evolution of the game is determined its initial state configuration normally set by the user, observing how it evolves and requires no further input. The patterns in this game include oscillators, still life and patterns that form spaceships across the board. Originally, no pattern could grow some set infinite limit. From a random pattern of living cell on a grid, an observer will see the population change as generations tick. The patterns emerging from simple rules are considered a form of beauty as small isolated patterns with no initial symmetry tend to become symmetrical. As one plays the game, there are rules to be observed. Each of the two dimensional orthogonal grid cells must be one of the two possible states i.e. alive or dead. Every cell has an interaction with eight neighbors arranged either horizontally, vertically or adjacent diagonally. The following transitions occur at each step time; any live cell that has less than two live neighbors die while that with two or three lives to next generation. Any cell with more than three neighbors dies of overcrowding while a dead cell with exactly three live neighbors becomes alive. B. a) Interdependence in the Game of Life can be exhibited in the development of cell automata. For instance, a cell is born if it has three neighbors while it stays alive if it has two or three live cells or else it dies. Also, a dead cell can be brought to live i.e. reproduced if it has exactly three live neighbors. This illustrates interdependent between live and dead cell since their life is dependent on one another. b) Spatial emergence and blinking which are forms of emergence can be illustrated by the Game of Life. In this game, population constantly changes as generations tick by. Forms of beauty emerge from simple rules forming patterns. Normally, small isolated patterns become symmetrical hence the symmetry increase richness leading to emergence of new generations. Some of the initial patterns burn out producing patterns oscillating forever producing a spaceship like pattern that travels away form initial position. This leads to many different patterns like blinkers that translate themselves across the board in form of spaceships. These patterns occur at different frequencies hence the idea of spatial emergence and blinking. C. An agent network theory refers to a computerized system comprising of multiple intelligent agents within a certain environment. These systems can be used to solve difficult systems that are impossible for a monolithic system. The kind of intelligent associated with these system include functional, methodic, procedural, finding and processing ability. The goal of such networks is to search for insights into the collective behavior of the agents in natural systems by obeying rules rather than solving practical problems. This systems can be applied in disaster management scenarios e.g. earthquake detection due to their ability to achieve automatic and dynamic ad self-healing scenarios. An agent-based network can help in disaster response since improving the information management during the disaster-collecting information, analyzing it, sharing it, and disseminating it to the right people at the right moment, will improve the response by helping humans make more informed decisions. Question 6 A. A root definition is a sentence that is expressed in a natural language and normally consist of elements according to the mnemonic CATWOE. In a related enterprise modelling, it can be stated as a controlled systems for developing models for corporation through consultations to ensure better understanding of all the units before any processes engineering. The CATOWOE in this case will be Customers=management, Actors=consultants, Transformation= management with and without overview, Weltanschauung= models to ensure better understanding, Owners= the management and Environmental constraints = business re-engineering processes. (Jackson, 2000) B. Root definitions are applied in the third stage of the seven stage methodology of the (SSM). This definitions are used the form the basis of the development of the system. They include statements and conceptual models achieved by consensus. C. When a root definition is devised in the form PQR, it therefore means that a system to do P, by means of Q to achieve R. This basically defines what to be done by the system (P), how it can be done (Q) and the reason for doing it defined by (R)” Question 7 A. Systems ambiguity can be defined as a situation where a system cannot be completed or implemented according to requirements of a customer and laid down procedures in a number of finite steps. Ambiguity in information systems project can occur in three ways i.e. ambiguity of information, context and relationship. Ambiguity manifests itself when systems analysts assume that what the user does not want is everything not mentioned in what the user does want. Users may ask for something to be in the system when in fact they really do not want or analysis may want to include something or functionality but with no idea on how to implement it or whether the user may like it hence the ambiguity. (Allen & Wilson, 2004) B. Vicker’s Appreciative Systems Approach focuses on both individual and group process their social contexts. The Appreciative systems approach recognizes both on individual and group’s contribution to social learning. Vickers focuses on facts and values, appreciation and action, evens and ideas. He also combines these attributes with standards and settings. Vickers argues that components of a human system, active individuals attributing meaning to their situation and hence make it possible to study such systems using natural science methods. These appreciative systems helps in understanding decision making process in human beings that are used to bear problems. These appreciative systems are normally interconnected to large standards of judgment by which human beings order and value their experience. (Jackson, 2000) C. The appreciative system of an individual helps to determine the way they see i.e. reality judgment and values (value judgment) various situations and conditions and how they make judgments and executes actions. This therefore determines these individual contribute to the development of the social world. According to Vickers, for human systems to achieve stability and be effective, the participant’s appreciative systems need to be shared so as to achieve mutual understanding. This is because human systems depend on shared understandings and cultures. Moreover, developments in human society and information systems depend on interactions the world of events and that of ideas. Therefore, this can be applied in solving ambiguity in information systems projects. (Allen & Wilson, 2004) Question 8 Soft systems methodologies are seen as learning and meaning development tool. Although it develops models, they are not supposed to represent the “real world”, but by using systems rules and principles, they allow one to structure your thinking about the real world. The models are neither descriptive nor normative, though they may carry elements of both. One of the interesting things about SSM is that it constrains one’s thinking in order for them to expand their thinking hence overwriting the idea that system thinking is expansive. In classical SSM, researchers start with a real-world problem. The study of the situation is done in a fairly unstructured way hence allowing developers develop some models of that situation. (Blackmore, 2010) The particular strength of SSM for evaluators is that it can be used to untangle the evaluative lessons from programs with multiple goals and multiple perspectives on these goals. It does so by developing specific perspectives on learning coupled with constructed models and then comparing them with real life situations. Most of the seven stages of SSM address the “real” world while some of them address a conceptual world. SSM therefore leads to rich picture building and hence one to examine its interventions, the social and political analysis. Thus illustrates the learning cycles present in a soft systems analysis and design activity. (Blackmore, 2010) Question 9 A. A comparison is between the conceptual and the real world models can be made in four different ways. (Conejero, 2010) These include; Unstructured discussions. This may include discussions such as what behaves similarly and what does not. Structured questioning of the model using a matrix approach. The matrix looks at each component and queries if it exists in real world, how it behaves, how its performance is identified and measured and if the process is good. Scenario or dynamic modelling. This includes comparing what actually does happen in the real world and what is present and establishing what is missing. Trying to model the real world using the same structure as the conceptual model B. The purpose of sensitivity analysis is to analyze what really matters in the decision problem and be able to construct a requisite decision model. In system design, sensitivity analysis is used to choose false-positive and false-negative rates for sensors and tests to ensure the quality of an information system. A key aspect of sensitivity analysis is the number of considered parameters. A three-way sensitivity analysis involves three parameters or variables changes at a time, i.e., we are only allowed to change three parameters in the network to ensure our query constraint. (Jackson, 2000) In software systems design, a three way sensitivity analysis helps in identifying the solution space of multiple parameter changes that would be needed to enforce a query constraint. It also helps in finding the optimal solution i.e. the one which disturbs the current probability distribution the least with respect to a specific measure of disturbance. This is done by selecting three variables and setting all other variables constant. The selected variables are varied from their lowest values, intermediate and to highest value and drawing the results. (Jackson, 2000) Question 10 The use of naked objects in systemic soft workflow modelling and implementation framework (SSWfMI) helps in the design of behaviorally-complete business projects. Systems developed using naked objects are more agile i.e. they can easily change future requirements. It also help s in workflow and their business process models to extract exact representation on the work flow between people and systems. Naked object also empower the user. They support functional modality by ensuring reduction I modality. Modal systems can infuriate users since user maybe be forced to complete one strict before initiating another. Naked objects provide mechanisms that help in reinforcing the model world metaphor and make it easy to adopt a conversational approach in workflow modelling. Lastly, modeling of naked objects improved communication between developers and users and also speed up the development process since the user interface is auto generated from the project definitions. (Jackson, 2000) During SSWfMI, activities are tested to determine their goals, and some of the activities are combined and some of them are decomposed. The activities and their goals are tested and mapped to UML use cases as one-to-one relationship. All use cases are combined in the use case diagram which consists of use cases and their actors. The use case diagram is part of the use case model which is representing the organizational business process and it will be the basis for modelling the object-oriented domain model. Each use case is modelled using UML activity diagram, sequence diagram, and class diagram. The activity diagram is used to model the functional, informational, behavioral, and organizational work flow perspectives. The sequence diagram is used to model the interaction between the use case objects. Finally, class diagrams for the static and organizational structures for each use case will be developed. (Allen & Wilson, 2004) The relevant system is modelled using a root definition and conceptual models. A variety of conceptual models are then developed to model the key activities in the system. From these, a simple Consensus Primary Task model (CPTM) is developed hence identifying the core activities that the first version of the system would need to support. SSM techniques can help the developer to identify a richer set of use cases than would otherwise be possible but developers with a full use case model still have many challenges ahead of them. The interest is on object oriented design and the view that all business behavior identified in the use case model should be encapsulated as methods on domain objects. (Allen & Wilson, 2004) Question 11 A. In systems theory, a Holon is something that has identity and integrity which is part of a larger system. It is simply a subsystem of a large system. Holons are independent units and handle contingencies without inquiry from the main large system. They are able to withstand disturbances. Example of holons include individual holons, social holons, artifacts and heaps. (Jackson, 2000) B. The mnemonic BATWOVE stands for B= Beneficiaries, A=Actors, T=Transformations, W= World-view, O= owners, V=Victims and E= Environmental constraints. (Jackson, 2000) Therefore, for a rail transport system, the BATWOVE will be; B = Beneficiaries include residents, employees A= Actors (Government Engineers and Staff) T= Transformations (Transforming the transport system through a reliable rail transport) W= World-View (Industrialization and economic growth in developed countries is supported by an efficient railway transport) O= Ownership (The Railway Corporation, Government) V= Victims (Resident around the areas to set up termini and rails tracks; they will be displaced) E= Environmental Issues (Air pollution by diesel wagons) Bibliography Allen, D., & Wilson, T. D. (2004). Action, interaction and the role of ambiguity in the introduction of mobile information systems in a UK Police Force. IFIP International Federation for Information Processing, 158, 15-36. Bak, P., Tang, C., & Wiesenfeld, K. (1998). Self-organized criticality. Physical Review A, 38, 364-374. Blackmore, C. (2010). Social learning systems and communities of practice. London: Springer. Conejero, J. M. (2010). The crosscutting pattern: a conceptual framework for the analysis of modularity across software development phases. Journal for Ambiguity as a Conceptual Framework for Design, 2(2), 444-502. Jackson, M. C. (2000). Systems approaches to management. New York: Kluwer Academic/Plenum. Joshi, K. (1999). Role conflict and role ambiguity in information systems design. Omega-international Journal of Management Science, 17(4), 369–380. Read More