13,323 research outputs found

    Happiness is assortative in online social networks

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    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

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    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 gig_i is almost independent of gig_i, 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

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    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

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    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

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    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

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    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

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    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 twt_w and random long-range jumps. While the time the walker needs to cover all the nodes increases with twt_w, the corresponding time for the edges displays a non monotonic behavior with a minimum for some nontrivial value of twt_w. This is a heterogeneity-induced effect that is not observed in homogeneous small-world networks. The optimal twt_w 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?

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    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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