Regional variation in social isolation amongst older Australians

Regional studies globally have a strong focus on understanding the causes of variation in the economic performance and wellbeing of regions and this emphasis acknowledges that the strength of the local or regional economy plays a determinant role in shaping quality of life. Regional research has been less active in considering spatial variation in other factors that are critical to individual and societal wellbeing. For example, the regional studies community has been absent from the debate on the social determinants of health and how these influences vary spatially. This paper considers the results of a cross sectional survey of Australians aged 65 and over that focussed on social connections and wellbeing. It examines regional variations in the incidence of social isolation within the older population. It finds that while the incidence of self-reported social isolation amongst older persons is broadly consistent with earlier studies, it demonstrates a spatial patterning that is unexpected. The paper considers community-building activities in addressing the impacts of social isolation, including the role of urban design, and suggests that there is a need to supplement the national overview presented there through more detailed studies focussed on individual localities.

Privacy architectures in social networks’ state-of-the-art survey

The use of social networking has exploded, with millions of people using various web- and mobile-based services around the world. This increase in social networking use has led to user anxiety related to privacy and the unauthorised exposure of personal information. Large-scale sharing in virtual spaces means that researchers, designers and developers now need to re-consider the issues and challenges of maintaining privacy when using social networking services. This paper provides a comprehensive survey of the current state-of-the-art privacy in social networks for both desktop and mobile uses and devices from various architectural vantage points. The survey will assist researchers and analysts in academia and industry to move towards mitigating many of the privacy issues in social networks.

Teacher peer support in social network sites

This paper describes the types of support that teachers are accessing through the Social Network Site (SNS) 'Facebook'. It describes six ways in which teachers support one another within online groups. It presents evidence from a study of a large, open group of teachers online over a twelve week period, repeated with multiple groups a year later over a one week period. The findings suggest that large open groups in SNSs can be a useful source of pragmatic advice for teachers but that these groups are rarely a place for reflection on or feedback about teaching practice.

Value Creation in Professional Service Processes. Propositions for Understanding Financial Value from a Customer Perspective

Many service management studies have suggested that service providers benefit from having long-term relationships with customers, but the argument from a customer perspective has been vague. However, especially in the business-to-business context, an analysis of financial value creation seems appropriate also from a customer perspective. Hence, the aim of this study is to develop a framework for understanding monetary value creation in professional service assignments from a customer perspective. The contribution of this study is an improved insight and framework for understanding financial value creation from a customer perspective in a professional service delivery process. The sources for monetary differences between transactional and long-term service providers are identified and quantified in case settings. This study contributes to the existing literature in service and relationship management by extending the customer’s viewpoint from perceived value to measurable monetary value. The contribution to the professional services lies in the process focus as opposed to the outcome focus, which is often accentuated in the existing professional services literature. The findings from the qualitative data suggest that a customer company may benefit from having an improved understanding of the service delivery (service assignment) process and the factors affecting the monetary value creation during the process. It is suggested that long-term relationships with service providers create financial value in the case settings in the short term. The findings also indicate that by using the improved understanding, a customer company can make more informed decisions when selecting a service provider for a specific assignment. Mirel Leino is associated with CERS, the Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration

Dimensions of University Student Learning in Medicine and Pharmacy

Study orientations in higher education consist of various dimensions, such as approaches to learning, conceptions of learning and knowledge (i.e. epistemologies), self-regulation, and motivation. They have also been measured in different ways. The main orientations typically reported are reproducing and meaning orientations. The present study explored dimensions of study orientations, focusing in particular on pharmacy and medicine. New versions of self-report instruments were developed and tested in various contexts and in two countries. Furthermore, the linkages between study orientations and students epistemological development were explored. The context of problem-based (PBL) small groups was investigated in order to better understand how collaboration contributes to the quality of learning. The participants of Study I (n=66) were pharmacy students, who were followed during a three-year professionally oriented program in terms of their study orientations and epistemologies. A reproducing orientation to studying diminished during studying, whereas only a few students maintained their original level of meaning orientation. Dualism was found to be associated with a reproducing orientation. In Study II practices associated with deep and surface approaches to learning were measured in two differing ways, in order to better distinguish between what students believed to be useful in studying, and the extent to which they applied their beliefs to practice when preparing for examinations. Differences between domains were investigated by including a sample of Finnish and Swedish medical students (n=956) and a Finnish non-medical sample of university students (n=865). Memorizing and rote learning appeared as differing components of a surface approach to learning, while understanding, relating, and critical evaluation of knowledge emerged as aspects of a deep approach to learning. A structural model confirmed these results in both student samples. Study III explored a wide variety of dimensions of learning in medical education. Swedish medical students (n=280) answered the questionnaire. The deep approach to learning was strongly related to collaboration and reflective learning, whereas the surface approach was associated with novice-like views of knowledge and the valuing of certain and directly applicable knowledge. PBL students aimed at understanding, but also valued the role of memorization. Study IV investigated 12 PBL tutorial groups of students (n=116) studying microbiology and pharmacology in a medical school. The educational application was expected to support a deep approach to learning: Group members course grades in a final examination were related to the perceived functioning of the PBL tutorial groups. Further, the quality of cases that had been used as triggers for learning, was associated with the quality of small group functioning. New dimensions of study orientations were discovered. In particular, novel, finer distinctions were found within the deep approach component. In medicine, critical evaluation of knowledge appeared to be less valued than understanding and relating. Further, collaboration appeared to be closely related to the deep approach, and it was also important in terms of successful PBL studying. The results of the studies confirmed the previously found associations between approaches to learning and study success, but showed interesting context- and subgroup-related differences in this respect. Students ideas about the nature of knowledge and their approaches to learning were shown to be closely related. The present study expanded our understanding of the dimensions of study orientations, of their development, and their contextual variability in pharmacy and medicine.

A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks

Our study concerns an important current problem, that of diffusion of information in social networks. This problem has received significant attention from the Internet research community in the recent times, driven by many potential applications such as viral marketing and sales promotions. In this paper, we focus on the target set selection problem, which involves discovering a small subset of influential players in a given social network, to perform a certain task of information diffusion. The target set selection problem manifests in two forms: 1) top-k nodes problem and 2) lambda-coverage problem. In the top-k nodes problem, we are required to find a set of k key nodes that would maximize the number of nodes being influenced in the network. The lambda-coverage problem is concerned with finding a set of k key nodes having minimal size that can influence a given percentage lambda of the nodes in the entire network. We propose a new way of solving these problems using the concept of Shapley value which is a well known solution concept in cooperative game theory. Our approach leads to algorithms which we call the ShaPley value-based Influential Nodes (SPINs) algorithms for solving the top-k nodes problem and the lambda-coverage problem. We compare the performance of the proposed SPIN algorithms with well known algorithms in the literature. Through extensive experimentation on four synthetically generated random graphs and six real-world data sets (Celegans, Jazz, NIPS coauthorship data set, Netscience data set, High-Energy Physics data set, and Political Books data set), we show that the proposed SPIN approach is more powerful and computationally efficient. Note to Practitioners-In recent times, social networks have received a high level of attention due to their proven ability in improving the performance of web search, recommendations in collaborative filtering systems, spreading a technology in the market using viral marketing techniques, etc. It is well known that the interpersonal relationships (or ties or links) between individuals cause change or improvement in the social system because the decisions made by individuals are influenced heavily by the behavior of their neighbors. An interesting and key problem in social networks is to discover the most influential nodes in the social network which can influence other nodes in the social network in a strong and deep way. This problem is called the target set selection problem and has two variants: 1) the top-k nodes problem, where we are required to identify a set of k influential nodes that maximize the number of nodes being influenced in the network and 2) the lambda-coverage problem which involves finding a set of influential nodes having minimum size that can influence a given percentage lambda of the nodes in the entire network. There are many existing algorithms in the literature for solving these problems. In this paper, we propose a new algorithm which is based on a novel interpretation of information diffusion in a social network as a cooperative game. Using this analogy, we develop an algorithm based on the Shapley value of the underlying cooperative game. The proposed algorithm outperforms the existing algorithms in terms of generality or computational complexity or both. Our results are validated through extensive experimentation on both synthetically generated and real-world data sets.

A Case Study in Matching Service Descriptions to Implementations in an Existing System

A number of companies are trying to migrate large monolithic software systems to Service Oriented Architectures. A common approach to do this is to first identify and describe desired services (i.e., create a model), and then to locate portions of code within the existing system that implement the described services. In this paper we describe a detailed case study we undertook to match a model to an open-source business application. We describe the systematic methodology we used, the results of the exercise, as well as several observations that throw light on the nature of this problem. We also suggest and validate heuristics that are likely to be useful in partially automating the process of matching service descriptions to implementations.

Determining Top K Nodes in Social Networks using the Shapley Value

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.

Efficient Algorithms for Combinatorial Auctions with Volume Discounts Arising in Web Service Composition

Web services are now a key ingredient of software services offered by software enterprises. Many standardized web services are now available as commodity offerings from web service providers. An important problem for a web service requester is the web service composition problem which involves selecting the right mix of web service offerings to execute an end-to-end business process. Web service offerings are now available in bundled form as composite web services and more recently, volume discounts are also on offer, based on the number of executions of web services requested. In this paper, we develop efficient algorithms for the web service composition problem in the presence of composite web service offerings and volume discounts. We model this problem as a combinatorial auction with volume discounts. We first develop efficient polynomial time algorithms when the end-to-end service involves a linear workflow of web services. Next we develop efficient polynomial time algorithms when the end-to-end service involves a tree workflow of web services.