108 research outputs found
The Directed Closure Process in Hybrid Social-Information Networks, with an Analysis of Link Formation on Twitter
It has often been taken as a working assumption that directed links in
information networks are frequently formed by "short-cutting" a two-step path
between the source and the destination -- a kind of implicit "link copying"
analogous to the process of triadic closure in social networks. Despite the
role of this assumption in theoretical models such as preferential attachment,
it has received very little direct empirical investigation. Here we develop a
formalization and methodology for studying this type of directed closure
process, and we provide evidence for its important role in the formation of
links on Twitter. We then analyze a sequence of models designed to capture the
structural phenomena related to directed closure that we observe in the Twitter
data
Coordination and Efficiency in Decentralized Collaboration
Environments for decentralized on-line collaboration are now widespread on
the Web, underpinning open-source efforts, knowledge creation sites including
Wikipedia, and other experiments in joint production. When a distributed group
works together in such a setting, the mechanisms they use for coordination can
play an important role in the effectiveness of the group's performance.
Here we consider the trade-offs inherent in coordination in these on-line
settings, balancing the benefits to collaboration with the cost in effort that
could be spent in other ways. We consider two diverse domains that each contain
a wide range of collaborations taking place simultaneously -- Wikipedia and
GitHub -- allowing us to study how coordination varies across different
projects. We analyze trade-offs in coordination along two main dimensions,
finding similar effects in both our domains of study: first we show that, in
aggregate, high-status projects on these sites manage the coordination
trade-off at a different level than typical projects; and second, we show that
projects use a different balance of coordination when they are "crowded," with
relatively small size but many participants. We also develop a stylized
theoretical model for the cost-benefit trade-off inherent in coordination and
show that it qualitatively matches the trade-offs we observe between
crowdedness and coordination.Comment: 10 pages, 6 figures, ICWSM 2015, in Proc. 9th International AAAI
Conference on Weblogs and Social Medi
Analysis of a continuous-time model of structural balance
It is not uncommon for certain social networks to divide into two opposing
camps in response to stress. This happens, for example, in networks of
political parties during winner-takes-all elections, in networks of companies
competing to establish technical standards, and in networks of nations faced
with mounting threats of war. A simple model for these two-sided separations is
the dynamical system dX/dt = X^2 where X is a matrix of the friendliness or
unfriendliness between pairs of nodes in the network. Previous simulations
suggested that only two types of behavior were possible for this system: either
all relationships become friendly, or two hostile factions emerge. Here we
prove that for generic initial conditions, these are indeed the only possible
outcomes. Our analysis yields a closed-form expression for faction membership
as a function of the initial conditions, and implies that the initial amount of
friendliness in large social networks (started from random initial conditions)
determines whether they will end up in intractable conflict or global harmony.Comment: 12 pages, 2 figure
On-line algorithms for robot navigation and server problems
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 83-88).by Jon Michael Kleinberg.M.S
Decompositions of Triangle-Dense Graphs
High triangle density -- the graph property stating that a constant fraction
of two-hop paths belong to a triangle -- is a common signature of social
networks. This paper studies triangle-dense graphs from a structural
perspective. We prove constructively that significant portions of a
triangle-dense graph are contained in a disjoint union of dense, radius 2
subgraphs. This result quantifies the extent to which triangle-dense graphs
resemble unions of cliques. We also show that our algorithm recovers planted
clusterings in approximation-stable k-median instances.Comment: 20 pages. Version 1->2: Minor edits. 2->3: Strengthened {\S}3.5,
removed appendi
Superlinear Scaling for Innovation in Cities
Superlinear scaling in cities, which appears in sociological quantities such
as economic productivity and creative output relative to urban population size,
has been observed but not been given a satisfactory theoretical explanation.
Here we provide a network model for the superlinear relationship between
population size and innovation found in cities, with a reasonable range for the
exponent.Comment: 5 pages, 5 figures, 1 table, submitted to Phys. Rev. E; references
corrected; figures corrected, references and brief discussion adde
Algorithmic Fairness from a Non-ideal Perspective
Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles
faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a
reinterpretation of impossibility results, and directions for future researc
The energy landscape of social balance
We model a close-knit community of friends and enemies as a fully connected
network with positive and negative signs on its edges. Theories from social
psychology suggest that certain sign patterns are more stable than others. This
notion of social "balance" allows us to define an energy landscape for such
networks. Its structure is complex: numerical experiments reveal a landscape
dimpled with local minima of widely varying energy levels. We derive rigorous
bounds on the energies of these local minima and prove that they have a modular
structure that can be used to classify them.Comment: 4 pages, 3 figure
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