Complex Systems Engineering for Rapid Computational Socio-Cultural Network Analysis and Decision Support Systems

The advent and adoption of internet-based social networking has significantly altered our daily lives. The educational community has taken notice of the positive aspects of social networking such as creation of blogs and to support groups of system designers going through the same challenges and difficulties. This paper introduces a social networking framework for collaborative education, design and modeling of the next generation of smarter products and services. Human behavior modeling in social networking application aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter products throughout the total system lifecycle. Social networks blend self-directed learning and prescribed, existing information. The selfdirected element creates interest within a learner and the ability to access existing information facilitates its transfer, and eventual retention of knowledge acquired. In conclusion, this research paper introduces the application of social-networking to design and modeling of products and services and provides a novel technology for facilitating the understanding of complex human behavior and to better identify crucial user needs.

[1]  S. Ziegler,et al.  The (mis)education of Generation M , 2007 .

[2]  Waldemar Karwowski,et al.  Interactive Management of Human Factors Knowledge for Human Systems Integration Using Systems Modeling Language , 2009, Inf. Syst. Manag..

[3]  Boris E. R. de Ruyter,et al.  New research perspectives on Ambient Intelligence , 2009, J. Ambient Intell. Smart Environ..

[4]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[5]  Marc Prensky,et al.  Digital game-based learning , 2000, CIE.

[6]  Sanford Friedenthal,et al.  A Practical Guide to SysML: The Systems Modeling Language , 2008 .

[7]  Yoav Shoham,et al.  Learning Information Retrieval Agents: Experiments with Automated Web Browsing , 1995 .

[8]  Diane J. Cook,et al.  Designing Smart Environments: A Paradigm Based on Learning and Prediction , 2005, PReMI.

[9]  Glen Allmendinger,et al.  Four strategies for the age of smart services. , 2005, Harvard business review.

[10]  Enrico Motta,et al.  Position Paper on Realizing Smart Products: Challenges for Semantic Web Technologies , 2009, SSN.

[11]  J. Meek,et al.  Facebook, social integration and informal learning at university: ‘It is more for socialising and talking to friends about work than for actually doing work’ , 2009 .

[12]  Wolfgang Maass,et al.  Preface to the Focus Theme Section: 'Smart Products' , 2008, Electron. Mark..

[13]  Max Mühlhäuser,et al.  Smart Products: An Introduction , 2007, AmI Workshops.

[14]  Guy Merchant,et al.  Looking from the inside out: academic blogging as new literacy , 2007 .

[15]  Waldemar Karwowski,et al.  Social Networking Applications: Smarter Product Design for Complex Human Behaviour Modeling , 2011, HCI.

[16]  Waldemar Karwowski,et al.  Collaborative systems engineering and social-networking approach to design and modelling of smarter products , 2011, Behav. Inf. Technol..

[17]  Derek K. Hitchins,et al.  Systems Engineering: A 21st Century Systems Methodology , 2007 .

[18]  Sanjay Chandrasekharan.  The semantic web: Knowledge representation and affordance , 2004 .