Synergistic Partitioning in Multiple Large Scale Social Networks

Abstract-Social networks have been part of people's daily life and plenty of users have registered accounts in multiple social networks. Interconnection among multiple social networks adds a multiplier effect to social applications when fully used. With the sharp expansion of network size, traditional standalone algorithms can no longer support computing on large scale networks while alternatively, distributed and parallel computing become a solution to utilizing the data-intensive information hidden in multiple social networks. As such, synergistic partitioning, which takes the relationships among different networks into consideration and focuses on partitioning the same nodes of different networks into same partitions. With that, the partitions containing the same nodes can be assigned to the same server to improve the data locality and reduce communication overhead among servers, which are very important for distributed applications. To date, there have been limited studies on multiple large scale network partitioning due to three major challenges: 1) the need to consider relationships across multiple networks given the existence of intricate interactions, 2) the difficulty for standalone programs to utilize traditional partitioning methods, 3) the fact that to generate balanced partitions is NP-complete. In this paper, we propose a novel framework to partition multiple social networks synergistically. In particular, we apply a distributed multilevel k-way partitioning method to divide the first network into k partitions. Based on the given anchor nodes which exist in all the social networks and the partition results of the first network, using MapReduce, we then develop a modified distributed multilevel partitioning method to divide other networks. Extensive experiments on two real data sets demonstrate that our method can significantly outperform baseline independentpartitioning method in accuracy and scalability

Selection pressure and organizational cognition: implications for the social determinants of health

We model the effects of Schumperterian 'selecton pressures' -- in particular Apartheid and the neoliberal 'market economy' -- on organizational cognition in minority communities, given the special role of culture in human biology. Our focus is on the dual-function social networks by which culture is imposed and maintained on individuals and by which immediate patterns of opportunity and threat are recognized and given response. A mathematical model based on recent advances in complexity theory displays a joint cross-scale linkage of social, individual central nervous system, and immune cognition with external selection pressure through mixed and synergistic punctuated 'learning plateaus.' This provides a natural mechanism for addressing the social determinants of health at the individual level. The implications of the model, particularly the predictions of synergistic punctuation, appear to be empirically testable

Synergistic Team Composition

Effective teams are crucial for organisations, especially in environments that require teams to be constantly created and dismantled, such as software development, scientific experiments, crowd-sourcing, or the classroom. Key factors influencing team performance are competences and personality of team members. Hence, we present a computational model to compose proficient and congenial teams based on individuals' personalities and their competences to perform tasks of different nature. With this purpose, we extend Wilde's post-Jungian method for team composition, which solely employs individuals' personalities. The aim of this study is to create a model to partition agents into teams that are balanced in competences, personality and gender. Finally, we present some preliminary empirical results that we obtained when analysing student performance. Results show the benefits of a more informed team composition that exploits individuals' competences besides information about their personalities

Immune cognition, social justice and asthma: structured stress and the developing immune system

We explore the implications of IR Cohen's work on immune cognition for understanding rising rates of asthma morbidity and mortality in the US. Immune cognition is conjoined with central nervous system cognition, and with the cognitive function of the embedding sociocultural networks by which individuals are acculturated and through which they work with others to meet challenges of threat and opportunity. Using a mathematical model, we find that externally- imposed patterns of 'structured stress' can, through their effect on a child's socioculture, become synergistic with the development of immune cognition, triggering the persistence of an atopic Th2 phenotype, a necessary precursor to asthma and other immune disease. Reversal of the rising tide of asthma and related chronic diseases in the US thus seems unlikely without a 21st Century version of the earlier Great Urban Reforms which ended the scourge of infectious diseases