Randi Karlsen

Review of Extracting Information From the Social Web for Health Personalization

In recent years the Web has come into its own as a social platform where health consumers are actively creating and consuming Web content. Moreover, as the Web matures, consumers are gaining access to personalized applications adapted to their health needs and interests. The creation of personalized Web applications relies on extracted information about the users and the content to personalize. The Social Web itself provides many sources of information that can be used to extract information for personalization apart from traditional Web forms and questionnaires. This paper provides a review of different approaches for extracting information from the Social Web for health personalization. We reviewed research literature across different fields addressing the disclosure of health information in the Social Web, techniques to extract that information, and examples of personalized health applications. In addition, the paper includes a discussion of technical and socioethical challenges related to the extraction of information for health personalization.

HealthTrust: A Social Network Approach for Retrieving Online Health Videos

Background Social media are becoming mainstream in the health domain. Despite the large volume of accurate and trustworthy health information available on social media platforms, finding good-quality health information can be difficult. Misleading health information can often be popular (eg, antivaccination videos) and therefore highly rated by general search engines. We believe that community wisdom about the quality of health information can be harnessed to help create tools for retrieving good-quality social media content. Objectives To explore approaches for extracting metrics about authoritativeness in online health communities and how these metrics positively correlate with the quality of the content. Methods We designed a metric, called HealthTrust, that estimates the trustworthiness of social media content (eg, blog posts or videos) in a health community. The HealthTrust metric calculates reputation in an online health community based on link analysis. We used the metric to retrieve YouTube videos and channels about diabetes. In two different experiments, health consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals reviewed 30 diabetes channels. Results HealthTrust may be used for retrieving online videos on diabetes, since it performed better than YouTube Search in most cases. Overall, of 20 potential channels, HealthTrust’s filtering allowed only 3 bad channels (15%) versus 8 (40%) on the YouTube list. Misleading and graphic videos (eg, featuring amputations) were more commonly found by YouTube Search than by searches based on HealthTrust. However, some videos from trusted sources had low HealthTrust scores, mostly from general health content providers, and therefore not highly connected in the diabetes community. When comparing video ratings from our reviewers, we found that HealthTrust achieved a positive and statistically significant correlation with professionals (Pearson r 10 = .65, P = .02) and a trend toward significance with health consumers (r 7 = .65, P = .06) with videos on hemoglobinA1 c, but it did not perform as well with diabetic foot videos. Conclusions The trust-based metric HealthTrust showed promising results when used to retrieve diabetes content from YouTube. Our research indicates that social network analysis may be used to identify trustworthy social media in health communities.

Personalized health applications in the Web 2.0: The emergence of a new approach

Health consumers have embraced the web to obtain access to health information and to socialize and share knowledge with peers. Additionally, the web has become a more interactive and rich platform with the integration of health applications and services, such as Personal Health Records. Some of these applications provide personalized interactions based on user specific characteristics. In this paper we provide an overview of Personalized Health Applications in the Web 2.0. We reviewed the health applications integrated in Google Health, Microsoft HealthVault and Facebook. We studied the goals of the applications and also the personalized feedback they provided.

An Adaptive Transactional System – Framework and Service Synchronization

The characteristics of advanced applications vary a lot and the transaction concept must adapt to fulfil the varying transactional requirements. However, current transaction services do not support the required flexibility in a principled way. We believe that the need for transaction service flexibility can be supported through reflection, where the system is capable of inspecting and changing its own behaviour. The first part of this paper describes a framework for such a reflective transactional system, in which different transaction services can be deployed and modified, and from where a suitable transaction service can be chosen for the execution of a transaction.

Privacy preserving health data processing

The usage of electronic health data from different sources for statistical analysis requires a toolset where the legal, security and privacy concerns have been taken into consideration. The health data are typically located at different general practices and hospitals. The data analysis consists of local processing at these locations, and the locations become nodes in a computing graph. To support the legal, security and privacy concerns, the proposed toolset for statistical analysis of health data uses a combination of secure multi-party computation (SMC) algorithms, symmetric and public key encryption, and public key infrastructure (PKI) with certificates and a certificate authority (CA). The proposed toolset should cover a wide range of data analysis with different data distributions. To achieve this, large set of possible SMC algorithms and computing graphs have to be supported.

ReflecTS: a flexible transaction service framework

Transactional requirements, from applications and execution environments, are varying and may exceed traditional ACID properties. We believe that transactional middleware platforms must be flexible in order to adapt to these requirements. Present systems are, however, inflexible with respect to such adaptations. ReflecTS is a flexible transaction processing platform maintaining an extensible number of concurrently running transaction services. This paper presents the architecture and the first prototype of ReflecTS, which focuses on a transaction service selection procedure. The selection procedure is based on XML-specifications of transactional requirements and transaction service descriptions-making the platform adjustable to varying requirements.

NFC provided user friendliness for technologically advanced services

This paper will discuss how an NFC enabled university campus can provide a wide range of user-friendly advanced services for its students and staff. These services combine information sources related to teaching, room reservation, social networking, proximity sensing, information collection and exchange, calendar services, event notifications, ticketing, loyalty cards, payment and more. In the ongoing NFC City Campus trial the usage of NFC enabled mobile phones, SIM cards as secure elements, and an adaptive infrastructure supporting information integration, demonstrates how NFC can contribute to the development of user friendly advanced services.

Personalized Photo Recommendation By Leveraging User Modeling On Social Network

An online social network is a digital representation of the set of human beings on the Internet. Social network services generate large amount of usage data; for example, Facebook defines detailed user profiles, and provides a platform for sharing information with a vast network of friends, and Flickr offers sophisticated ways for sharing and searching for photos. In this paper, We propose cross-domain user profile modeling that acquires background knowledge from Linked Open Data and measures user interests. We infer the users preferences by analyzing her Facebook profile, and expand it by linking it to Flickr in order to recommend socially relevant photos.

Flexible transaction processing in the Argos middleware

Transactional requirements, from new application domains and execution environments, are varying and may exceed traditional ACID properties. We believe that transactional middleware platforms must be flexible in order to adapt to varying transactional requirements. This is to some extend demonstrated within Web service environments where support for both ACID and long-running business transactions are provided. This paper presents an extension along the path to flexible transaction processing in the form of the Argos Transaction Layer. As opposed to present systems, the Argos Transaction Layer offers the potentiality to hotdeploy an extensible number of concurrently running transaction services, each providing different transactional guarantees. Currently, the Transaction Layer offers two services, one serving the ACID properties of distributed transactions, and one supporting long-running business transactions based on the use of compensation.

Promoting levels of openness on component-based adaptable middleware

It is widely accepted that middleware is an important architectural element which facilitates the development of software systems. In this paper we propose a novel approach for designing middleware. It is based on hardware motherboards and two distinct views with a clear separation of concerns. The view for middleware designer (MD-view) is concerned with all complex details of middleware structure and the view for middleware users (MU-view) is only concerned with an abstract set of open architectural elements that can be used to customize the middleware.