Efficient techniques for time-constrained information dissemination using location-based social networks

Social networks have undergone an explosive growth in recent years. They constitute a central part of users׳ everyday lives as they are used as major tools for the spread of information, ideas and notifications among the members of the network. In this work we investigate the use of location-based social networks as a medium of emergency notification, for efficient dissemination of emergency information among members of the social network under time constraints. Our objective is the following: given a location-based social network comprising a number of mobile users, the social relationships among the users, the set of recipients, and the corresponding timeliness requirements, our goal is to select an appropriate subset of users so that the spread of information is maximized, time constraints are satisfied and costs are considered. We propose LATITuDE, our system that investigates the interactions among the members of the social network to infer their social relationships, and develop scalable dissemination mechanisms that select the most efficient set of users to initiate the dissemination process in order to maximize the information reach among the appropriate receivers within a time window. Our detailed experimental results illustrate that our approach is practical, effectively addresses the problem of informing the appropriate set of users within a deadline when an emergency event occurs, uses a small number of messages, and consistently outperforms its competitors.     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

Social networks,communication styles,and learning performance in a CSCL community

The aim of this study is to empirically investigate the relationships between communication styles, social networks, and learning performance in a computer-supported collaborative learning (CSCL) community. Using social network analysis (SNA) and longitudinal survey data, we analyzed how 31 distributed learners developed collaborative learning social networks, when they had work together on the design of aerospace systems using online collaboration tools. The results showed that both individual and structural factors (i.e., communication styles and a pre-existing friendship network) significantly affected the way the learners developed collaborative learning social networks. More specifically, learners who possessed high willingness to communicate (WTC) or occupied initially peripheral network positions were more likely to explore new network linkages. We also found that the resultant social network properties significantly influenced learners’ performance to the extent that central actors in the emergent collaborative social network tended to get higher final grades. The study suggests that communication and social networks should be central elements in a distributed learning environment. We also propose that the addition of personality theory (operationalized here as communication styles) to structural analysis (SNA) contributes to an enhanced picture of how distributed learners build their social and intellectual capital in the context of CSCL.     

Providing Adaptive Health Updates Across the Personal Social Network

This article presents research conducted to establish how information is shared across the personal social network in the sensitive context of a health crisis. We worked with parents of very sick babies who were cared for in a hospital's Neonatal Unit (NNU). Through a combination of interviews, a focus group, and surveys, we developed a user model of the information that parents wanted to share, and how they adapted this information to individual recipients. We then developed a prototype software tool which created adaptive updates for members of the parents' social network. The updates contained summaries of large volumes of complex medical data about the baby, nonmedical information about the parents, and practical information about the hospital. Updates were automatically adapted to individual members of parents' social networks, based on our user model. The tool was evaluated in a large NNU in the United Kingdom with parents of babies who were currently being cared for in the unit. We found that parents adapted the information that they shared about themselves and their babies based on the emotional proximity of their network members. They gave most detail to those who were emotionally closest to them and least to those who were less close. Parents also adapted information content to the recipient's tendency to worry and empathize. Two adaptive strategies were deployed by parents, (a) benign deceit—not telling the whole truth—and (b) promotion of empathetic members of the social network to a higher level of emotional proximity, so that they were given more information. We generated a number of directions for future work, and issues to consider around designing adaptive mediated communications systems for sensitive contexts. These include the potential to generalize our model to other medical contexts and considerations to apply when deliberately designing deceit into adaptive systems.     

弱连接对不同类型在线社交网络信息传播范围的影响研究

按照连接强度的不同,在线社交网络节点间的连接可以分为强连接和弱连接,可以通过网络上两个节点的邻居相对重叠来测量连接强度。实验表明,弱连接对于信息传播范围的影响与具体的网络类型有关系,在基于信息交换的在线社交网络中,例如移动电话通信网络、Wiki投票网络,移去弱连接并不会对信息收敛时传播的范围产生明显的影响;而在基于合作关系形成的在线社交网络中,例如Youtube、Facebook、CDBLP合作网,移去弱连接对信息传播的范围有明显的阻碍作用。     

The co-learning process in healthcare professionals: Assessing user satisfaction in virtual communities of practice

Communities of practice are nowadays an important concept in the healthcare sector. Particularly, the intensive use of ICT has allowed their creation into a virtual environment – Virtual Communities of Practice (VCoPs) developing optimal conditions to make possible the collaborative learning process. The VCoPs antecedents can be situated on social network phenomenon, where individuals with different traits but a common interest/objective are linked, use ICT potency (especially social media) to interchange information, experiences and contents among them. And as a result, people create and share knowledge, and learn collaboratively. VCoP users have a higher satisfaction level in the collaborative learning process when they can: (1) Achieve benefits related to patient diagnosis and treatment (cost reductions, faster management, quality and accuracy of diagnosis, etc.); (2) Increase the share capital of participants and creating networks of trusted individuals. Given the interest in this topic, the objective of this work is to identify the factors that determine user satisfaction in relation to Community Practice (CoP) and the process of building shared knowledge. For this, a sample of 130 Spanish health professionals participating in an online community, and developed in a virtual community of practice, is discussed. The results obtained from an analysis of logistic regression show evidence of the perception of efficiency and effectiveness in collaboration with the members of the VCoP as positively influencing the perceived satisfaction with the CoP. Also, the degree of individual participation in the community affects the degree of perceived satisfaction. The conclusions provide interesting strategic recommendations in the management process of the CoP.     

Sonification of a network’s self-organized criticality for real-time situational awareness

Communication networks involve the transmission and reception of large volumes of data. Research indicates that network traffic volumes will continue to increase. These traffic volumes will be unprecedented and the behaviour of global information infrastructures when dealing with these data volumes is unknown. It has been shown that complex systems (including computer networks) exhibit self-organized criticality under certain conditions. Given the possibility in such systems of a sudden and spontaneous system reset the development of techniques to inform system administrators of this behaviour could be beneficial. This article focuses on the combination of two dissimilar research concepts, namely sonification (a form of auditory display) and self-organized criticality (SOC). A system is described that sonifies in real time an information infrastructure’s self-organized criticality to alert the network administrators of both normal and abnormal network traffic and operation. It is shown how the system makes changes in a system’s SOC readily perceptible. Implications for how such a system may support real-time situational awareness and post hoc incident analysis are discussed.     

Demographics and Behavior of the Chilean Internet Population

When a computer network connects people or organizations, it is a social network. Yet the study of such computer-supported social networks has not received as much attention as studies of human-computer interaction, online person-to-person interaction, and computer-supported communication within small groups. We argue the usefulness of a social network approach for the study of computer-mediated communication. We review some basic concepts of social network analysis, describe how to collect and analyze social network data, and demonstrate where social network data can be, and have been, used to study computer-mediated communication. Throughout, we show the utility of the social network approach for studying computer-mediated communication, be it in computer-supported cooperative work, in virtual community, or in more diffuse interactions over less bounded systems such as the Internet.     

Group awareness of social and cognitive performance in a CSCL environment: Effects of a peer feedback and reflection tool

A peer feedback tool (Radar) and a reflection tool (Reflector) were used to enhance group performance in a computer-supported collaborative learning environment. Radar allows group members to assess themselves and their fellow group members on six traits related to social and cognitive behavior. Reflector stimulates group members to reflect on their past, present and future group functioning, stimulating them to set goals and formulate plans to improve their social and cognitive performance. The underlying assumption was that group performance would be positively influenced by making group members aware of how they, their peers and the whole group perceive their social and cognitive behavior in the group. Participants were 108 fourth-year high school students working in dyads, triads and groups of four on a collaborative writing task, with or without the tools. Results demonstrate that awareness stimulated by the peer feedback and reflection tools enhances group-process satisfaction and social performance of CSCL-groups.