The influence of system designer intention over collaborative tagging. an analysis of tagging behaviour in CiteULike and Delicious

Tagging provides support for retrieval and categorization of online content depending on users' tag choice. A number of models of tagging behaviour have been proposed to identify factors that are considered to affect taggers, such as users' tagging history. In this paper, we use Semiotics Analysis and Activity theory, to study the effect the system designer has over tagging behaviour. The framework we use shows the components that comprise the tagging system and how they interact together to direct tagging behaviour. We analysed two collaborative tagging systems: CiteULike and Delicious by studying their components by applying our framework. Using datasets from both systems, we found that 35% of CiteULike users did not provide tags compared to only 0.1% of Delicious users. This was directly linked to the type of tools used by the system designer to support tagging

Analysing the factors that influence tag choice based on semiotic analysis and activity theory

Social tagging has become very popular around the Internet as well as in research. The main idea behind tagging is to allow users to provide metadata to the web content from their perspective to facilitate categorization and retrieval. There are many factors that influence users' tag choice. Many studies have been conducted to reveal these factors by analysing tagging data. This paper uses two theories to identify these factors, namely the semiotics theory and activity theory. The former treats tags as signs and the latter treats tagging as an activity. The paper uses both theories to analyse tagging behaviour by explaining all aspects of a tagging system, including tags, tagging system components and the tagging activity. The theoretical analysis produced a framework that was used to identify a number of factors. These factors can be considered as categories that can be consulted to redirect user tagging choice in order to support particular tagging behaviour, such as cross-lingual tagging

A CONCEPTUAL LIFE EVENT FRAMEWORK FOR GOVERNMENT-TO-CITIZEN ELECTRONIC SERVICES PROVISION

In recent years, life event approach has been widely used by governments all over the world for designing and providing web services to citizens through their e-government portals. Despite the wide usage of this approach, there is still a challenge of how to use this approach to design e-government portals in order to automatically provide personalised services to citizens. We propose a conceptual framework for e-government service provision based on life event approach and the use of citizen profile to capture the citizen needs, since the process of finding Web services from a government-to-citizen (G2C) system involves understanding the citizens’ needs and demands, selecting the relevant services, and delivering services that matches the requirements. The proposed framework that incorporates the citizen profile is based on three components that complement each other, namely, anticipatory life events, non-anticipatory life events and recurring services

Semiotic approach to a practice-oriented knowledge transfer

Knowledge is a valuable asset in organisations that has become significant as a strategic resource in the information age. Many studies have focused on managing knowledge in organisations. In particular, knowledge transfer has become a significant issue concerned with the movement of knowledge across organisational boundaries. One way to capture knowledge in a transferrable form is through practice. In this paper, we discuss how organisations can transfer knowledge through practice effectively and propose a model for a semiotic approach to practice-oriented knowledge transfer. In this model, practice is treated as a sign that represents knowledge, and its localisation is analysed as a semiotic process

Development of Tumor-Specific Caffeine-Potentiated Chemotherapy Using Span 80 Nano-Vesicles DDS

Osteosarcoma cases with metastasis have poor prognosis in general. Recently, caffeinepotentiated chemotherapy, which is chemotherapy with caffeine dosage against malignancies, has manifested potently high efficacy as well as diverse effects. Recently, we demonstrated that nonionic vesicles prepared from Span 80 have promising physicochemical properties, which let them an attractive option besides the common liposomes. Here, we manifested the tumor-specific caffeine-potentiated chemotherapy against osteosarcoma in murine model employing a novel drug delivery system (DDS) with Span 80 nano-vesicles. C3H/HeJ mice underwent transplantation of LM8 osteosarcoma cell line and then were doped with therapeutic agents. Caffeine was employed as an enhancer in addition to ifosfamide (IFO) as the antitumor agent. in vitro, the united administration of IV + CV revealed significant induction of tumor apoptosis in the early phase. In vivo study manifested that IV + CV-administration markedly decreased the tumor volume as well as the viable tumor area than in the other groups. No marked organ damage was observed in the IV or IV + CV groups as well as fertility injury and/or malformations in their progeny. This novel DDS might have the importance for clinical application in primary tumors as well as the metastatic osteosarcoma

Modeling building semantics: providing feedback and sustainability

Even minor changes in user activity can bring about significant energy savings within built space. Many building performance assessment methods have been developed, however these often disregard the impact of user behavior (i.e. the social, cultural and organizational aspects of the building). Building users currently have limited means of determining how sustainable they are, in context of the specific building structure and/or when compared to other users performing similar activities, it is therefore easy for users to dismiss their energy use. To support sustainability, buildings must be able to monitor energy use, identify areas of potential change in the context of user activity and provide contextually relevant information to facilitate persuasion management. If the building is able to provide users with detailed information about how specific user activity that is wasteful, this should provide considerable motivation to implement positive change. This paper proposes using a dynamic and temporal semantic model, to populate information within a model of persuasion, to manage user change. By semantically mapping a building, and linking this to persuasion management we suggest that: i) building energy use can be monitored and analyzed over time; ii) persuasive management can be facilitated to move user activity towards sustainability

Designing persuasive third party applications for social networking services based on the 3D-RAB model

The use of social networks services for promoting business, teaching, learning, persuasion and spread of information continues to attract attention as most social networking services (SNSs) now allow third party applications to operate on their sites. In the field of persuasive technology, the ability of SNSs to build relationships among their users and create momentum and enthusiasm through rapid cycles also give it a greater advantage over other persuasive technology approaches. In this paper we discuss the 3-dimensional relationship between attitude and behavior (3D-RAB) model, and demonstrate how it can be used in designing third-party persuasive applications in SNSs by considering external factors which affects persuasive strategies

Aligning IS Programs with Industry: Linking Business Analysis Curricula Design with the Professional Body

Aligning information systems (IS) solutions with business goals and needs are crucial for IS activities. IS professionals who are able to work closely with both the business and technical staff are key enablers of business-IT alignment. IS programs in higher education (HE) institutions have a long tradition of enabling graduates to develop the appropriate skills needed for their future careers. Yet, organizations are still having difficulty finding graduates who possess both the knowledge and skills that are best suited to their specific requirements. Prior studies suggest that IS curricula are often ill-matched with industry/business needs. We report on the business analysis curricula (re)design undertaken to align it with a key professional body for the IS industry. We present the approaches taken in the (re)designed module, and provide a discussion of the wider implications for IS curricula design. The results show a positive outcome for the HE and professional body partnership

Culture, cognition and e-commerce behavior

Existing research has given little attention to the relationship between culture characteristics and consumer’s internal beliefs particularly in the pre-purchase stage, and how this relationship affects consumer’s purchase decision. This paper considers the theory of cognitive dissonance and its extended model (the 3D-RAB), as a means to study the current distribution of consumer’s pre-purchase cognitive dissonance, which allows us to investigate the effects of culture characteristics on this distribution. Results revealed that individualism versus collectivism and high power distance dimensions, from Hofstede’s cultural model, influence consumer’s pre-purchase cognitive dissonance. These dimensions must be considered in the design of e-commerce website, by tailoring motivational/influences methods and techniques to reflect targeted consumers culture

VaR and ES forecasting via recurrent neural network-based stateful models

Due to the widespread and quickly escalating effects of large negative returns, as well as due to the increase in the importance of regulatory framework for financial institutions, the accurate measurement of financial risks has become a relevant question in the academia and industry. This paper proposes three novel models based on stateful Recurrent Neural Networks (RNN) and Feed-Forward Neural Networks (FNN) to build forecasts for Value-at-Risk (VaR) and Expected Shortfall (ES). We apply the models to six asset return time series spanning over more than 20 years. Our results reveal that the RNN-based stateful models generally outperform the non-stateful RNN models and econometric benchmark models including rolling window models, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH)-type models, and Generalized Autoregressive Score (GAS) models, in terms of VaR and ES forecasting