13,323 research outputs found
Happiness is assortative in online social networks
Social networks tend to disproportionally favor connections between
individuals with either similar or dissimilar characteristics. This propensity,
referred to as assortative mixing or homophily, is expressed as the correlation
between attribute values of nearest neighbour vertices in a graph. Recent
results indicate that beyond demographic features such as age, sex and race,
even psychological states such as "loneliness" can be assortative in a social
network. In spite of the increasing societal importance of online social
networks it is unknown whether assortative mixing of psychological states takes
place in situations where social ties are mediated solely by online networking
services in the absence of physical contact. Here, we show that general
happiness or Subjective Well-Being (SWB) of Twitter users, as measured from a 6
month record of their individual tweets, is indeed assortative across the
Twitter social network. To our knowledge this is the first result that shows
assortative mixing in online networks at the level of SWB. Our results imply
that online social networks may be equally subject to the social mechanisms
that cause assortative mixing in real social networks and that such assortative
mixing takes place at the level of SWB. Given the increasing prevalence of
online social networks, their propensity to connect users with similar levels
of SWB may be an important instrument in better understanding how both positive
and negative sentiments spread through online social ties. Future research may
focus on how event-specific mood states can propagate and influence user
behavior in "real life".Comment: 17 pages, 9 figure
Betweenness centrality correlation in social networks
Scale-free (SF) networks exhibiting a power-law degree distribution can be
grouped into the assortative, dissortative and neutral networks according to
the behavior of the degree-degree correlation coefficient. Here we investigate
the betweenness centrality (BC) correlation for each type of SF networks. While
the BC-BC correlation coefficients behave similarly to the degree-degree
correlation coefficients for the dissortative and neutral networks, the BC
correlation is nontrivial for the assortative ones found mainly in social
networks. The mean BC of neighbors of a vertex with BC is almost
independent of , implying that each person is surrounded by almost the
same influential environments of people no matter how influential the person
is.Comment: 4 pages, 4 figures, 1 tabl
Robustness of correlated networks against propagating attacks
We investigate robustness of correlated networks against propagating attacks
modeled by a susceptible-infected-removed model. By Monte-Carlo simulations, we
numerically determine the first critical infection rate, above which a global
outbreak of disease occurs, and the second critical infection rate, above which
disease disintegrates the network. Our result shows that correlated networks
are robust compared to the uncorrelated ones, regardless of whether they are
assortative or disassortative, when a fraction of infected nodes in an initial
state is not too large. For large initial fraction, disassortative network
becomes fragile while assortative network holds robustness. This behavior is
related to the layered network structure inevitably generated by a rewiring
procedure we adopt to realize correlated networks.Comment: 6 pages, 13 figure
Weighted Assortative And Disassortative Networks Model
Real-world networks process structured connections since they have
non-trivial vertex degree correlation and clustering. Here we propose a toy
model of structure formation in real-world weighted network. In our model, a
network evolves by topological growth as well as by weight change. In addition,
we introduce the weighted assortativity coefficient, which generalizes the
assortativity coefficient of a topological network, to measure the tendency of
having a high-weighted link between two vertices of similar degrees. Network
generated by our model exhibits scale-free behavior with a tunable exponent.
Besides, a few non-trivial features found in real-world networks are reproduced
by varying the parameter ruling the speed of weight evolution. Most
importantly, by studying the weighted assortativity coefficient, we found that
both topologically assortative and disassortative networks generated by our
model are in fact weighted assortative.Comment: 8 pages, minor clarifications, to be published in Physica
Marriage and Fertility in a Catholic Society: Eighteenth-Century Quebec
There are similarities and differences in marriage and fertility behavior between early North American societies and their modern counterparts. This paper investigates the quantitative importance of differential fecundity, assortative matching, and marriage market search frictions in affecting marriage and fertility behavior in a Catholic society, 18th century Quebec. The model may provide an explanation for both the historic and current experience.
Jamming in complex networks with degree correlation
We study the effects of the degree-degree correlations on the pressure
congestion J when we apply a dynamical process on scale free complex networks
using the gradient network approach. We find that the pressure congestion for
disassortative (assortative) networks is lower (bigger) than the one for
uncorrelated networks which allow us to affirm that disassortative networks
enhance transport through them. This result agree with the fact that many real
world transportation networks naturally evolve to this kind of correlation. We
explain our results showing that for the disassortative case the clusters in
the gradient network turn out to be as much elongated as possible, reducing the
pressure congestion J and observing the opposite behavior for the assortative
case. Finally we apply our model to real world networks, and the results agree
with our theoretical model
Intermittent exploration on a scale-free network
We study an intermittent random walk on a random network of scale-free degree
distribution. The walk is a combination of simple random walks of duration
and random long-range jumps. While the time the walker needs to cover all
the nodes increases with , the corresponding time for the edges displays a
non monotonic behavior with a minimum for some nontrivial value of . This
is a heterogeneity-induced effect that is not observed in homogeneous
small-world networks. The optimal increases with the degree of
assortativity in the network. Depending on the nature of degree correlations
and the elapsed time the walker finds an over/under-estimate of the degree
distribution exponent.Comment: 12 pages, 3 figures, 1 table, published versio
Multidimensional perfectionism and assortative mating: A perfect date?
Assortative mating has been found regarding personality traits, personal attitudes and values, and cognitive abilities, but so far no study has investigated assortative mating regarding multidimensional perfectionism. A total of 422 participants from a non-commercial panel (mean age = 36.0 years) completed measures of self-oriented, other-oriented, and socially prescribed perfectionism and rated the attractiveness of four potential dating partners (“dates”): a self-oriented, an other-oriented, a socially prescribed, and a non-perfectionist date. Results showed that all perfectionist dates were seen as less attractive than the non-perfectionist date. This effect, however, was moderated by self-oriented and other-oriented perfectionism. Participants high in self-oriented perfectionism found all three perfectionist dates more attractive than participants low in self-oriented perfections. Participants high in other-oriented perfectionism found the self-oriented perfectionist date more attractive, and the non-perfectionist date less attractive than participants low in other-oriented perfectionism. The findings are discussed with respect to assortative mating, the social disconnection model of perfectionism, and the heritability of perfectionism
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