Opening the flow of citizen engagement: An exploratory study of social networking services as a potential vehicle for e-participation in the City and County of Honolulu

Peer-reviewed journal articleThis study examined the use of Social Networking Services (SNS) by policymakers in the City and County of Honolulu. Interviews identified policymakers’ main reasons for using SNS, examined how SNS was integrated into the policymaking process, and also highlighted issues faced in deploying SNS for government services. The City and County informally initiated use of SNS in 2008, and use remained at an early stage of integration into business processes and operations at the time of this study. Government-operated SNS was primarily used as a one-way-information-based service. In this early stage, SNS was not being used to directly promote e-participation initiatives, although potential future uses were discussed. Government officials noted a spectrum of desired expectations regarding future development of SNS. We recommend an agency-wide use policy be created to provide for consistency of use across administrations and that a formal pilot study, addressing the perspectives of multiple stakeholders, be initiated

Webometrics benefitting from web mining? An investigation of methods and applications of two research fields

Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms

Information quality assessment in e-learning systems.

E-learning systems provide a promising solution as an information exchanging channel. Improved technology could mean faster and easier access to information but does not necessarily ensure the quality of this information. Therefore it is essential to develop valid and reliable methods of quality measurement and carry out careful information quality evaluations. Information quality frameworks are developed to measure the quality of information systems, generally from the designers¿ viewpoint. The recent proliferation of e-services, and e-learning particularly, raises the need for a new quality framework in the context of e-learning systems. The main contribution of this thesis is to propose a new information quality framework, with 14 information quality attributes grouped in three quality dimensions: intrinsic, contextual representation and accessibility. We report results based on original questionnaire data and factor analysis. Moreover, we validate the proposed framework using an empirical approach. We report our validation results on the basis of data collected from an original questionnaire and structural equation modeling (SEM) analysis, confirmatory factor analysis (CFA) in particular. However, it is difficult to measure information quality in an e-learning context because the concept of information quality is complex and it is expected that the measurements will be multidimensional in nature. Reliable measures need to be obtained in a systematic way, whilst considering the purpose of the measurement. Therefore, we start by adopting a Goal Question Metrics (GQM) approach to develop a set of quality metrics for the identified quality attributes within the proposed framework. We then define an assessment model and measurement scheme, based on a multi element analysis technique. The obtained results can be considered to be promising and positive, and revealed that the framework and assessment scheme could give good predictions for information quality within e-learning context. This research generates novel contributions as it proposes a solution to the problems raised from the absence of consensus regarding evaluation standards and methods for measuring information quality within an e-learning context. Also, it anticipates the feasibility of taking advantage of web mining techniques to automate the retrieval process of the information required for quality measurement. This assessment model is useful to e-learning systems designers, providers and users as it gives a comprehensive indication of the quality of information in such systems, and also facilitates the evaluation, allows comparisons and analysis of information quality