48 research outputs found
Social Diffusion and Global Drift on Networks
We study a mathematical model of social diffusion on a symmetric weighted
network where individual nodes' states gradually assimilate to local social
norms made by their neighbors' average states. Unlike physical diffusion, this
process is not state conservational and thus the global state of the network
(i.e., sum of node states) will drift. The asymptotic average node state will
be the average of initial node states weighted by their strengths. Here we show
that, while the global state is not conserved in this process, the inner
product of strength and state vectors is conserved instead, and perfect
positive correlation between node states and local averages of their
self/neighbor strength ratios always results in upward (or at least neutral)
global drift. We also show that the strength assortativity negatively affects
the speed of homogenization. Based on these findings, we propose an adaptive
link weight adjustment method to achieve the highest upward global drift by
increasing the strength-state correlation. The effectiveness of the method was
confirmed through numerical simulations and implications for real-world social
applications are discussed.Comment: 7 pages, 3 figures; to appear in Phys. Rev.
Success and luck in creative careers
Luck is considered to be a crucial ingredient to achieve impact in all
creative domains, despite their diversity. For instance, in science, the movie
industry, music, and art, the occurrence of the highest impact work and of a
hot streak within a creative career are very difficult to predict. Are there
domains that are more prone to luck than others? Here, we provide new insights
on the role of randomness in impact in creative careers in two ways: (i) we
systematically untangle luck and individual ability to generate impact in the
movie, music, and book industries, and in science, and compare the luck factor
between these fields; (ii) we show the limited predictive power of
collaboration networks to predict career hits. Taken together, our analysis
suggests that luck consistently affects career impact across all considered
sectors and improves our understanding in pinpointing the key elements in the
prediction of success
Historical comparison of gender inequality in scientific careers across countries and disciplines
There is extensive, yet fragmented, evidence of gender differences in
academia suggesting that women are under-represented in most scientific
disciplines, publish fewer articles throughout a career, and their work
acquires fewer citations. Here, we offer a comprehensive picture of
longitudinal gender discrepancies in performance through a bibliometric
analysis of academic careers by reconstructing the complete publication history
of over 1.5 million gender-identified authors whose publishing career ended
between 1955 and 2010, covering 83 countries and 13 disciplines. We find that,
paradoxically, the increase of participation of women in science over the past
60 years was accompanied by an increase of gender differences in both
productivity and impact. Most surprisingly though, we uncover two gender
invariants, finding that men and women publish at a comparable annual rate and
have equivalent career-wise impact for the same size body of work. Finally, we
demonstrate that differences in dropout rates and career length explain a large
portion of the reported career-wise differences in productivity and impact.
This comprehensive picture of gender inequality in academia can help rephrase
the conversation around the sustainability of women's careers in academia, with
important consequences for institutions and policy makers.Comment: 23 pages, 4 figures, and S
Growing Urban Bicycle Networks
Cycling is a promising solution to unsustainable urban transport systems.
However, prevailing bicycle network development follows a slow and piecewise
process, without taking into account the structural complexity of
transportation networks. Here we explore systematically the topological
limitations of urban bicycle network development. For 62 cities we study
different variations of growing a synthetic bicycle network between an
arbitrary set of points routed on the urban street network. We find initially
decreasing returns on investment until a critical threshold, posing fundamental
consequences to sustainable urban planning: Cities must invest into bicycle
networks with the right growth strategy, and persistently, to surpass a
critical mass. We also find pronounced overlaps of synthetically grown networks
in cities with well-developed existing bicycle networks, showing that our model
reflects reality. Growing networks from scratch makes our approach a generally
applicable starting point for sustainable urban bicycle network planning with
minimal data requirements.Comment: Main text: 14 pages, 7 figures. Website: http://growbike.ne
Career on the Move: Geography, Stratification, and Scientific Impact
Changing institutions is an integral part of an academic life. Yet little is known about the mobility patterns of scientists at an institutional level and how these career choices affect scientific outcomes. Here, we examine over 420,000 papers, to track the affiliation information of individual scientists, allowing us to reconstruct their career trajectories over decades. We find that career movements are not only temporally and spatially localized, but also characterized by a high degree of stratification in institutional ranking. When cross-group movement occurs, we find that while going from elite to lower-rank institutions on average associates with modest decrease in scientific performance, transitioning into elite institutions does not result in subsequent performance gain. These results offer empirical evidence on institutional level career choices and movements and have potential implications for science policy
Emergence of good conduct, scaling and Zipf laws in human behavioral sequences in an online world
We study behavioral action sequences of players in a massive multiplayer
online game. In their virtual life players use eight basic actions which allow
them to interact with each other. These actions are communication, trade,
establishing or breaking friendships and enmities, attack, and punishment. We
measure the probabilities for these actions conditional on previous taken and
received actions and find a dramatic increase of negative behavior immediately
after receiving negative actions. Similarly, positive behavior is intensified
by receiving positive actions. We observe a tendency towards anti-persistence
in communication sequences. Classifying actions as positive (good) and negative
(bad) allows us to define binary 'world lines' of lives of individuals.
Positive and negative actions are persistent and occur in clusters, indicated
by large scaling exponents alpha~0.87 of the mean square displacement of the
world lines. For all eight action types we find strong signs for high levels of
repetitiveness, especially for negative actions. We partition behavioral
sequences into segments of length n (behavioral `words' and 'motifs') and study
their statistical properties. We find two approximate power laws in the word
ranking distribution, one with an exponent of kappa-1 for the ranks up to 100,
and another with a lower exponent for higher ranks. The Shannon n-tuple
redundancy yields large values and increases in terms of word length, further
underscoring the non-trivial statistical properties of behavioral sequences. On
the collective, societal level the timeseries of particular actions per day can
be understood by a simple mean-reverting log-normal model.Comment: 6 pages, 5 figure