Suicide ideation of individuals in online social networks

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.Comment: 4 figures, 9 table

Clustering and the hyperbolic geometry of complex networks

Clustering is a fundamental property of complex networks and it is the mathematical expression of a ubiquitous phenomenon that arises in various types of self-organized networks such as biological networks, computer networks or social networks. In this paper, we consider what is called the global clustering coefficient of random graphs on the hyperbolic plane. This model of random graphs was proposed recently by Krioukov et al. as a mathematical model of complex networks, under the fundamental assumption that hyperbolic geometry underlies the structure of these networks. We give a rigorous analysis of clustering and characterize the global clustering coefficient in terms of the parameters of the model. We show how the global clustering coefficient can be tuned by these parameters and we give an explicit formula for this function.Comment: 51 pages, 1 figur

Does bariatric surgery prior to total hip or knee arthroplasty reduce post-operative complications and improve clinical outcomes for obese patients? Systematic review and meta-analysis.

AIMS: Our aim was to determine whether, based on the current literature, bariatric surgery prior to total hip (THA) or total knee arthroplasty (TKA) reduces the complication rates and improves the outcome following arthroplasty in obese patients. METHODS: A systematic literature search was undertaken of published and unpublished databases on the 5 November 2015. All papers reporting studies comparing obese patients who had undergone bariatric surgery prior to arthroplasty, or not, were included. Each study was assessed using the Downs and Black appraisal tool. A meta-analysis of risk ratios (RR) and 95% confidence intervals (CI) was performed to determine the incidence of complications including wound infection, deep vein thrombosis (DVT), pulmonary embolism (PE), revision surgery and mortality. RESULTS: From 156 potential studies, five were considered to be eligible for inclusion in the study. A total of 23 348 patients (657 who had undergone bariatric surgery, 22 691 who had not) were analysed. The evidence-base was moderate in quality. There was no statistically significant difference in outcomes such as superficial wound infection (relative risk (RR) 1.88; 95% confidence interval (CI) 0.95 to 0.37), deep wound infection (RR 1.04; 95% CI 0.65 to 1.66), DVT (RR 0.57; 95% CI 0.13 to 2.44), PE (RR 0.51; 95% CI 0.03 to 8.26), revision surgery (RR 1.24; 95% CI 0.75 to 2.05) or mortality (RR 1.25; 95% CI 0.16 to 9.89) between the two groups. CONCLUSION: For most peri-operative outcomes, bariatric surgery prior to THA or TKA does not significantly reduce the complication rates or improve the clinical outcome. This study questions the previous belief that bariatric surgery prior to arthroplasty may improve the clinical outcomes for patients who are obese or morbidly obese. This finding is based on moderate quality evidence. Cite this article: Bone Joint J 2016;98-B:1160-6

Timing interactions in social simulations: The voter model

The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table

Mining Diversity on Social Media Networks

The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. We first lay out two criteria that capture the semantic meaning of diversity, and then propose a compliant definition which is simple enough to embed the idea. Based on the approach, we can measure not only a user’s sociality and interest diversity but also a social media’s user diversity. An efficient top-k diversity ranking algorithm is developed for computation on dynamic networks. Experiments on both synthetic and real social media datasets give interesting results, where individual nodes identified with high diversities are intuitive

Detection of atherosclerotic cardiovascular disease influences the perceived need for aggressive lipid management

Background and aims Overt atherosclerotic cardiovascular disease (ASCVD) warrants aggressive lipid lowering. Imaging for ambiguous symptoms suggesting ischemia or for clarification of CV risk in asymptomatic individuals often uncovers previously unknown ASCVD. Guidelines do not provide clear recommendations for aggressive lipid lowering in such cases. We explored physicians' perception, as influenced by tests that detect ASCVD, regarding appropriateness of getting to lipid goals and for theoretically accessing proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i). Methods A questionnaire was developed including cases of low to high CV risk, chronic kidney disease (CKD) or type 2 diabetes mellitus (T2DM). Each case was considered with or without angina symptoms and, in turn, whether testing identified previously unknown advanced, early/subclinical or no ASCVD. Synthesis of responses was facilitated by using a scale for perceived appropriateness from 1 (lowest) to 9 (highest). Results Getting to goal and, if not achieved by statins and/or ezetimibe, accessing PCSK9i was considered appropriate in patients with T2DM with preclinical or advanced ASCVD, patients with moderate or high CV risk and advanced ASCVD, patients with CKD or low CV risk with angina symptoms and advanced ASCVD. For most of the remaining cases adding PCSK9i was considered only possibly appropriate. Conclusions Physicians' perception of appropriateness for achieving lipid goals, including access to PCSK9i, is markedly influenced by detection of previously unknown ASCVD. Since these commonly encountered scenarios do not clearly meet current indications for PCSK9i, our data identify pressing areas requiring further research

Effectiveness of bisphosphonates on nonvertebral and hip fractures in the first year of therapy: The risedronate and alendronate (REAL) cohort study

INTRODUCTION: Randomized clinical trials have shown that risedronate and alendronate reduce fractures among women with osteoporosis. The aim of this observational study was to observe, in clinical practice, the incidence of hip and nonvertebral fractures among women in the year following initiation of once-a-week dosing of either risedronate or alendronate. METHODS: Using records of health service utilization from July 2002 through September 2004, we created two cohorts: women (ages 65 and over) receiving risedronate (n = 12,215) or alendronate (n = 21,615). Cox proportional hazard modeling was used to compare the annual incidence of nonvertebral fractures and of hip fractures between cohorts, adjusting for potential differences in risk factors for fractures. RESULTS: There were 507 nonvertebral fractures and 109 hip fractures. Through one year of therapy, the incidence of nonvertebral fractures in the risedronate cohort (2.0%) was 18% lower (95% CI 2% – 32%) than in the alendronate cohort (2.3%). The incidence of hip fractures in the risedronate cohort (0.4%) was 43% lower (95% CI 13% – 63%) than in the alendronate cohort (0.6%). These results were consistent across a number of sensitivity analyses. CONCLUSION: Patients receiving risedronate have lower rates of hip and nonvertebral fractures during their first year of therapy than patients receiving alendronate

Temporal networks of face-to-face human interactions

The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface statistical features to dynamical processes on empirical temporal networks. We discuss how simple dynamical processes can be used as probes to expose important features of the interaction patterns, such as burstiness and causal constraints. We show that simulating dynamical processes on empirical temporal networks can unveil differences between datasets that would otherwise look statistically similar. Moreover, we argue that, due to the temporal heterogeneity of human dynamics, in order to investigate the temporal properties of spreading processes it may be necessary to abandon the notion of wall-clock time in favour of an intrinsic notion of time for each individual node, defined in terms of its activity level. We conclude highlighting several open research questions raised by the nature of the data at hand.Comment: Chapter of the book "Temporal Networks", Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saram\"aki, Jari (Eds.