Global network structure of dominance hierarchy of ant workers

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks.     

Influencing dynamics on social networks without knowledge of network microstructure

Social network-based information campaigns can be used for promoting beneficial health behaviours and mitigating polarization (e.g. regarding climate change or vaccines). Network-based intervention strategies typically rely on full knowledge of network structure. It is largely not possible or desirable to obtain population-level social network data due to availability and privacy issues. It is easier to obtain information about individuals’ attributes (e.g. age, income), which are jointly informative of an individual’s opinions and their social network position. We investigate strategies for influencing the system state in a statistical mechanics based model of opinion formation. Using synthetic and data-based examples we illustrate the advantages of implementing coarse-grained influence strategies on Ising models with modular structure in the presence of external fields. Our work provides a scalable methodology for influencing Ising systems on large graphs and the first exploration of the Ising influence problem in the presence of ambient (social) fields. By exploiting the observation that strong ambient fields can simplify control of networked dynamics, our findings open the possibility of efficiently computing and implementing public information campaigns using insights from social network theory without costly or invasive levels of data collection.     

Social network architecture and the maintenance of deleterious cultural traits

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a ‘cultural load’ of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual''s network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.     

The incremental validity of the dark triad in predicting driving aggression

This research tested the association between the Dark Triad and driving aggression as well as the incremental validity of the Dark Triad in predicting aggressive driving and the mediation role of the Dark Triad in the relationship between Big Five personality factors and aggressive driving. 274 undergraduate students in Study 1 and 95 amateur drivers in Study 2 completed measures of the Dark Triad (Machiavellianism, Narcissism and Psychopathy), the Big Five personality factors and the aggressive driving expression. Results showed that all the Dark Triad traits were related to aggressive driving behavior in both Study 1 and Study 2 and that the Dark Triad predicted driving aggression after the effect of the Big five personality factors was controlled, with Psychopathy being the strongest predictor of driving aggression in both Study 1 and Study 2. Machiavellianism and Psychopathy mediated the relationship between Emotional Stability, Agreeableness, Conscientiousness on one hand and aggressive driving on the other hand.     

The effect of network mixing patterns on epidemic dynamics and the efficacy of disease contact tracing

In networks, nodes may preferentially contact other nodes with similar (assortatively mixed) or dissimilar (disassortatively mixed) numbers of contacts. Different patterns of contact support different epidemic dynamics, potentially affecting the efficacy of control measures such as contact tracing, which aims to identify and isolate nodes with infectious contacts. We used stochastic simulations to investigate the effects of mixing patterns on epidemic dynamics and contact-tracing efficacy. For uncontrolled epidemics, outbreaks occur at lower infection rates for more assortatively mixed networks, with faster initial epidemic growth rate and shorter epidemic duration than for disassortatively mixed networks. Contact tracing performs better for assortative mixing where epidemic size is large and tracing rate low, but it performs better for disassortative mixing at higher contact rates. For assortatively mixed networks, disease spreads first to highly connected nodes, but this is balanced by contact tracing quickly identifying these same nodes. The converse is true for disassortative mixing, where both disease and tracing are less likely to target highly connected nodes. For small epidemics, contact tracing is more effective on disassortative networks due to the greater resilience of assortative networks to link removal. Multi-step contact tracing is more effective than single-step tracing for assortative mixing, but this effect is smaller for disassortatively mixed networks.     

多项目关键链进度优化算法分析

针对多项目进度优化问题,综合应用关键链和社会认知优化算法,保证了多项目计划在不确定环境下的稳定运行。文章首先在保证进度工期最短的前提下,进行了多项目的排序,进而确定对后续项目的影响。通过实例应用于多项目进度管理中,为工程决策与管理者全面而准确地进行多项目管理、掌握项目进度、保证项目如期完工,以及对后续项目进行合理地预测提供了依据。并讨论了应用关键链方法进一步研究的方向。     

Democratizing the scientific space: The constellation of new epistemic strategies around the emerging metaphor of socially embedded autonomy

The question of the democratization of the scientific space is a complex topic which goes beyond instrumental, normative and substantive arguments justifying civic participation, to include feminist, epistemological and sociological critical theory on the construction of knowledge, ignorance and agency. An exploration across different disciplines and contexts suggests that these different fields share a culture which increasingly employs the metaphor of socially embedded autonomy. Democratization emerges as multi-directional and multi-functional, whether in the reflection by the scientific community on the social conventions of the scientific space to strengthen their objective autonomy and withstand the manufacture of ignorance around invested interests; or in research design where interdisciplinary approaches around transdisciplinary themes such as gender and climate change incorporate citizen participation in the research process, benefitting from local knowledge about particular contexts.     

The effects of R&D subsidies and network embeddedness on R&D output: evidence from the German biotech industry

Although policy makers subsidize firms’ R&D projects to increase innovational output in an industry, region, or country, it remains unclear whether such subsidization triggers additional R&D efforts or crowds out private investments. To address this question, we assess the effectiveness of subsidization for individual and collaborative research in the German biotech industry while also examining the relevance of network embeddedness for patent output. Our results indicate that subsidies do lead to increased patent output, with additional benefits from involvement in more than one project. However, the amount of money is only significant under certain circumstances. Also, it is higher degree centrality in the firm network that significantly increases R&D success.     

The role of online social networks for divorced Saudi women in the face of social,psychological, economic,and legal challenges

This research examines the supporting role social networks provide to divorced Saudi women in the face of social, economic, psychological, and legal challenges. An online survey with open and closed ended questions was created to address the following research question: What support do online social networks provide to divorced Saudi women in contemporary Saudi Arabian society in the face of social, economic, psychological, and legal challenges?” The survey was completed online by 248 divorced Saudi women. Quantitative analysis of closed-ended survey responses was applied to the dataset followed by a qualitative thematic analysis of respondents' responses to open-ended questions. Survey findings identified the following areas of medium to high social network support experienced by divorced Saudi women: social outcast avoidance, relationship management with former husband, income assistance, emotional support, confidence building, and depression management. Findings also revealed areas where social networks provided only low levels of support with respect to social, economic, psychological, and legal challenges. The research contributes new insights into the supporting role of social networks for divorced Saudi women and their potential to leverage personal life and identity development in the face of social stigmatization and societal marginalization. This work advances research relevant to media studies, woman's studies, and cultural studies.