Spreading in Social Systems: Reflections

In this final chapter, we consider the state-of-the-art for spreading in social systems and discuss the future of the field. As part of this reflection, we identify a set of key challenges ahead. The challenges include the following questions: how can we improve the quality, quantity, extent, and accessibility of datasets? How can we extract more information from limited datasets? How can we take individual cognition and decision making processes into account? How can we incorporate other complexity of the real contagion processes? Finally, how can we translate research into positive real-world impact? In the following, we provide more context for each of these open questions.Comment: 7 pages, chapter to appear in "Spreading Dynamics in Social Systems"; Eds. Sune Lehmann and Yong-Yeol Ahn, Springer Natur

Alone in the Crowd: The Structure and Spread of Loneliness in a Large Social Network

The discrepancy between an individual’s loneliness and the number of connections in a social network is well documented, yet little is known about the placement of loneliness within, or the spread of loneliness through, social networks. We use network linkage data from the population-based Framingham Heart Study to trace the topography of loneliness in people’s social networks and the path through which loneliness spreads through these networks. Results indicated that loneliness occurs in clusters, extends up to three degrees of separation, is disproportionately represented at the periphery of social networks, and spreads through a contagious process. The spread of loneliness was found to be stronger than the spread of perceived social connections, stronger for friends than family members, and stronger for women than for men. The results advance our understanding of the broad social forces that drive loneliness and suggest that efforts to reduce loneliness in our society may benefit by aggressively targeting the people in the periphery to help repair their social networks and to create a protective barrier against loneliness that can keep the whole network from unraveling.Sociolog

Guiding Dynamic Symbolic Execution Toward Unverified Program Executions

Most techniques to detect program errors, such as testing, code reviews, and static program analysis, do not fully verify all possible executions of a program. They leave executions unverified when they do not check certain properties, fail to verify properties, or check properties under certain unsound assumptions such as the absence of arithmetic overflow. In this paper, we present a technique to complement partial verification results by automatic test case generation. In contrast to existing work, our technique supports the common case that the verification results are based on unsound assumptions. We annotate programs to reflect which executions have been verified, and under which assumptions. These annotations are then used to guide dynamic symbolic execution toward unverified program executions. Our main technical contribution is a code instrumentation that causes dynamic symbolic execution to abort tests that lead to verified executions, to prune parts of the search space, and to prioritize tests that cover more properties that are not fully verified. We have implemented our technique for the .NET static analyzer Clousot and the dynamic symbolic execution tool Pex. It produces smaller test suites (by up to 19.2%), covers more unverified executions (by up to 7.1%), and reduces testing time (by up to 52.4%) compared to combining Clousot and Pex without our technique

A Study of Concurrency Bugs and Advanced Development Support for Actor-based Programs

The actor model is an attractive foundation for developing concurrent applications because actors are isolated concurrent entities that communicate through asynchronous messages and do not share state. Thereby, they avoid concurrency bugs such as data races, but are not immune to concurrency bugs in general. This study taxonomizes concurrency bugs in actor-based programs reported in literature. Furthermore, it analyzes the bugs to identify the patterns causing them as well as their observable behavior. Based on this taxonomy, we further analyze the literature and find that current approaches to static analysis and testing focus on communication deadlocks and message protocol violations. However, they do not provide solutions to identify livelocks and behavioral deadlocks. The insights obtained in this study can be used to improve debugging support for actor-based programs with new debugging techniques to identify the root cause of complex concurrency bugs.Comment: - Submitted for review - Removed section 6 "Research Roadmap for Debuggers", its content was summarized in the Future Work section - Added references for section 1, section 3, section 4.3 and section 5.1 - Updated citation

Model of Genetic Variation in Human Social Networks

Social networks exhibit strikingly systematic patterns across a wide range of human contexts. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "Attract and Introduce" model with two simple forms of heterogeneity that generates significant heritability as well as other important network features. We show that the model is well suited to real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.Comment: Additional materials related to the paper are available at http://jhfowler.ucsd.ed

Hemodynamic benefits of the Toronto stentless valve

AbstractWe report on 254 consecutive patients (170 male, 84 female) undergoing aortic valve replacement with the Toronto SPV Stentless Valve (St. Jude Medical, Inc., St. Paul, Minn.). Mean age (± standard deviation) was 62.1 ± 11.6 years. Three patients (1%) received sizes 21 or 22 mm, 24 (9%) received size 23 mm, and 227 patients (89%) received sizes 25, 27, or 29 mm. Serial echocardiography was used to assess valve performance during a 3-year follow-up. Mean gradient decreased by 35.8% ( p < 0.0001; 95% confidence interval -39.6%, -31.7%) from postoperative values to the 3- to 6-month follow-up and by 6.1% ( p = 0.004; 95% confidence interval -10.1%, -2%) at each subsequent interval; effective orifice area increased by 17.2% ( p = 0.0001; 95% confidence interval 12.0%, 22.6%) initially and by 4.4% ( p < 0.001; 95% confidence interval 1.8%, 7.0%) thereafter. At 2 years of follow-up, mean gradient was 3.3 ± 2.1 mm Hg and mean effective orifice area was 2.2 ± 0.8 cm 2 . Studies on left ventricular mass were carried out on 84 patients. Left ventricular mass decreased by 14.3% (37.8 ± 57.9 gm; p < 0.0001; 95% confidence interval -53.7, -21.9 gm) and left ventricular mass index decreased by 15.2% (21.1 ± 30.5 gm/m 2; p < 0.0001; 95% confidence interval -29.5, -12.7 gm/m 2) from postoperative values to the 3- to 6-month follow-up interval. The reduction in residual gradient and potential regression in left ventricular hypertrophy may have a beneficial prognostic implication. We believe that the unique stentless design of the Toronto SPV Stentless Valve allows this to occur. (J T horac C ardiovasc S urg 1996;112:431-46