26 research outputs found
Multilayer network decoding versatility and trust
In the recent years, the multilayer networks have increasingly been realized
as a more realistic framework to understand emergent physical phenomena in
complex real world systems. We analyze a massive time-varying social data drawn
from the largest film industry of the world under multilayer network framework.
The framework enables us to evaluate the versatility of actors, which turns out
to be an intrinsic property of lead actors. Versatility in dimers suggests that
working with different types of nodes are more beneficial than with similar
ones. However, the triangles yield a different relation between type of
co-actor and the success of lead nodes indicating the importance of higher
order motifs in understanding the properties of the underlying system.
Furthermore, despite the degree-degree correlations of entire networks being
neutral, multilayering picks up different values of correlation indicating
positive connotations like trust, in the recent years. Analysis of weak ties of
the industry uncovers nodes from lower degree regime being important in linking
Bollywood clusters. The framework and the tools used herein may be used for
unraveling the complexity of other real world systems.Comment: 16 pages, 5 figure
Optimization of synchronizability in multiplex networks
We investigate the optimization of synchronizability in multiplex networks
and demonstrate that the interlayer coupling strength is the deciding factor
for the efficiency of optimization. The optimized networks have homogeneity in
the degree as well as in the betweenness centrality. Additionally, the
interlayer coupling strength crucially affects various properties of individual
layers in the optimized multiplex networks. We provide an understanding to how
the emerged network properties are shaped or affected when the evolution
renders them better synchronizable.Comment: 6 pages and 6 figure
Uncovering Randomness and Success in Society
An understanding of how individuals shape and impact the evolution of society
is vastly limited due to the unavailability of large-scale reliable datasets
that can simultaneously capture information regarding individual movements and
social interactions. We believe that the popular Indian film industry,
'Bollywood', can provide a social network apt for such a study. Bollywood
provides massive amounts of real, unbiased data that spans more than 100 years,
and hence this network has been used as a model for the present paper. The
nodes which maintain a moderate degree or widely cooperate with the other nodes
of the network tend to be more fit (measured as the success of the node in the
industry) in comparison to the other nodes. The analysis carried forth in the
current work, using a conjoined framework of complex network theory and random
matrix theory, aims to quantify the elements that determine the fitness of an
individual node and the factors that contribute to the robustness of a network.
The authors of this paper believe that the method of study used in the current
paper can be extended to study various other industries and organizations.Comment: 39 pages, 12 figures, 14 table
Social patterns revealed through random matrix theory
Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play
Codon based co-occurrence network motifs in human mitochondria
The nucleotide polymorphism in human mitochondrial genome (mtDNA) tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, we constructed genome-wide nucleotide co-occurrence networks using a massive data consisting of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns between codon and non-codon positions. It was interesting to report a different evolution of Asian genomes than those of the rest which is divulged by network motifs. We found evidence that mtDNA undergoes substantial amounts of adaptive evolution, a finding which was supported by a number of previous studies. The dominance of higher order motifs indicated the importance of long-range nucleotide co-occurrence in genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analyses manifested that codon position co-evolution is very well conserved across human sub-populations and independently maintained within human sub-populations implying the selective role of evolutionary processes on codon position co-evolution. Ergo, this study provided a framework to investigate cooperative genomic interactions which are critical in underlying complex mitochondrial evolution
Optimization of synchronizability in multiplex networks
We investigate the optimization of synchronizability in multiplex networks and demonstrate that the interlayer coupling strength is the deciding factor for the efficiency of optimization. The optimized networks have homogeneity in the degree as well as in the betweenness centrality. Additionally, the interlayer coupling strength crucially affects various properties of individual layers in the optimized multiplex networks. We provide an understanding as to how the emerged network properties are shaped or affected when the evolution renders them better synchronizable
Bollywood movie repository data
<p>Please cite us as:</p>
<p>1. Sarika Jalan, Camellia Sarkar, Anagha Madhusudanan, Sanjiv K. Dwivedi. Uncovering randomness and success in society. PLoS ONE 9, e88249 (2014).<br>DOI: 10.1371/journal.pone.0088249</p>
<p>2. Camellia Sarkar, Sarika Jalan. Social patterns revealed through random matrix theory. EPL 108, 48003 (2014).<br>DOI: 10.1209/0295-5075/108/48003</p