Massive user enabled evolving web system

UnrestrictedUser-Generated Content Websites[1], or "social media" Websites[2], such as YouTube[3] or Flickr[4], have gained tremendous success for their ability to use user-generated meta-content to further their user experience. However, current UGC developments resemble the ad-hoc Web developments of the 1990s and Software developments of the 1960s[5]. Past history has shown what these approaches can lead to, and there are already failed UGC developments caused by these uninformed approaches. In this thesis, the research will be geared towards finding a theoretical framework that target the unique behavior of UGCs, and discovering means to remedy their problems and complexities.; The ad-hoc approaches to UGC developments are caused by a lack of fundamental understanding these systems' behaviors. This work will illustrate that these UGCs are Massive User Enabled Evolving Web Systems (MUEEWS), where user-generated meta-content are used to evolve system functionalities. By making users a key stakeholder in enabling its functionalities, MUEEWS creates an evolution that occurs during the usage phase of the software. Current Software and Web Engineering models do not explain the effects of this phenomenon[6], and current UGC research target specific applications that are difficult to apply extensively. Since the evolutions of the functionalities are dependent on the contributions of very large group, MUEEWScontains a number of collective action issues that can create system failures.; The lack of fundamental understanding creates many complexities for MUEEWS in both the development and usage phase. Therefore, for the improvement of future MUEEWS developments, this work will provide a theoretical framework to guide its development and manage its complexities. The theoretical framework is evaluated using functional complexity analysis and validated through simulations and test scenarios. The findings illustrate that the application of the theoretical framework can greatly reduce the probability of system failure in MUEEWS and can improve its meta-content and system functionality performances. This thesis focuses on the users' contributions, and how to leverage those contributions to improve system functionality. Since the current field of UGC is not focused on theoretical or system approaches of MUEEWS, this research topic can be used to make various important contributions to the field of UGC