Information Systems and Healthcare XX: Toward Seamless Healthcare with Software Agents

Healthcare processes are frequently fragmented and often badly supported with IT. Inter- and intra-organizational communication and media frictions complicate the continuous provision of information according to the principle of information logistics. Based on extensive literature review, we present the vision of seamless healthcare with horizontally and vertically integrated healthcare processes enabled by seamless IT support. Its implementation requires the establishment of a communication infrastructure and the deployment of adequate standards in healthcare. There are already comprehensive approaches for dealing with integrating heterogeneous information systems. However, they lack a common communication infrastructure and do not support proactivity and flexibility which are dominant characteristics in healthcare. We propose a software agent-based approach for realizing the vision of seamless healthcare. We present a corresponding implementation for integrating heterogeneous information systems in the context of the German Health Telematics Infrastructure. Based on the concept and the implementation, we show that the modular approach is capable of supporting a wide range of different applications. We furthermore outline which facets of an agent-based solution could be implemented in an operative real-world environment. In closing we derive implications for IT decision makers in healthcare and show directions for future approaches for reducing information logistics related deficits in healthcare

Between the Information Economy and Student Recruitment: Present Conjuncture and Future Prospects

In university programs and curricula, in general we react to the need to meet market needs. We respond to market stimulus, or at least try to do so. Consider now an inverted view. Consider our data and perspectives in university programs as reflecting and indeed presaging economic trends. In this article I pursue this line of thinking. I show how various past events fit very well into this new view. I provide explanation for why some technology trends happened as they did, and why some current developments are important now.Comment: 18 pages, 4 figure

CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

Cashtag piggybacking: uncovering spam and bot activity in stock microblogs on Twitter

Microblogs are increasingly exploited for predicting prices and traded volumes of stocks in financial markets. However, it has been demonstrated that much of the content shared in microblogging platforms is created and publicized by bots and spammers. Yet, the presence (or lack thereof) and the impact of fake stock microblogs has never systematically been investigated before. Here, we study 9M tweets related to stocks of the 5 main financial markets in the US. By comparing tweets with financial data from Google Finance, we highlight important characteristics of Twitter stock microblogs. More importantly, we uncover a malicious practice - referred to as cashtag piggybacking - perpetrated by coordinated groups of bots and likely aimed at promoting low-value stocks by exploiting the popularity of high-value ones. Among the findings of our study is that as much as 71% of the authors of suspicious financial tweets are classified as bots by a state-of-the-art spambot detection algorithm. Furthermore, 37% of them were suspended by Twitter a few months after our investigation. Our results call for the adoption of spam and bot detection techniques in all studies and applications that exploit user-generated content for predicting the stock market

Customer adoption of p2p mobile payment systems: The role of perceived risk

Peer-to-peer (P2P) payments are experiencing strong growth due to the notable interest in mobile payments and the effect of the COVID-19 pandemic on individuals’ behaviours. This research analyses the success factors in customers’ adoption of Bizum, a prototypical P2P mobile payment system already used by almost half of the Spanish population. Using data from real Bizum users and structural equation modelling, it was confirmed that: (1) customers’ attitudes and perceptions of control over the mobile app increased use and WOM intentions; (2) the subjective norm (i.e., social approval) is not important for the adoption of this P2P service; (3) the direct effect of perceived risk on behavioural intentions is not significant and that perceived risk is moderated by perceived security, such that its negative effects are significant when users perceive lower levels of security; (4) age and gender do not significantly influence adoption, which suggests that the service might be used by a wide spectrum. Finally, from a practical viewpoint, this research contributes to the understanding of the success factors underlying P2P platforms, which can help managers better develop their market penetration strategies in a highly competitive sector

Spotting the diffusion of New Psychoactive Substances over the Internet

Online availability and diffusion of New Psychoactive Substances (NPS) represent an emerging threat to healthcare systems. In this work, we analyse drugs forums, online shops, and Twitter. By mining the data from these sources, it is possible to understand the dynamics of drugs diffusion and their endorsement, as well as timely detecting new substances. We propose a set of visual analytics tools to support analysts in tackling NPS spreading and provide a better insight about drugs market and analysis