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Signed graph embedding: when everybody can sit closer to friends than enemies

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 Publication date 2014
and research's language is English




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Signed graphs are graphs with signed edges. They are commonly used to represent positive and negative relationships in social networks. While balance theory and clusterizable graphs deal with signed graphs to represent social interactions, recent empirical studies have proved that they fail to reflect some current practices in real social networks. In this paper we address the issue of drawing signed graphs and capturing such social interactions. We relax the previous assumptions to define a drawing as a model in which every vertex has to be placed closer to its neighbors connected via a positive edge than its neighbors connected via a negative edge in the resulting space. Based on this definition, we address the problem of deciding whether a given signed graph has a drawing in a given $ell$-dimensional Euclidean space. We present forbidden patterns for signed graphs that admit the introduced definition of drawing in the Euclidean plane and line. We then focus on the $1$-dimensional case, where we provide a polynomial time algorithm that decides if a given complete signed graph has a drawing, and constructs it when applicable.



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We are given an integer $d$, a graph $G=(V,E)$, and a uniformly random embedding $f : V rightarrow {0,1}^d$ of the vertices. We are interested in the probability that $G$ can be realized by a scaled Euclidean norm on $mathbb{R}^d$, in the sense that there exists a non-negative scaling $w in mathbb{R}^d$ and a real threshold $theta > 0$ so that [ (u,v) in E qquad text{if and only if} qquad Vert f(u) - f(v) Vert_w^2 < theta,, ] where $| x |_w^2 = sum_i w_i x_i^2$. These constraints are similar to those found in the Euclidean minimum spanning tree (EMST) realization problem. A crucial difference is that the realization map is (partially) determined by the random variable $f$. In this paper, we consider embeddings $f : V rightarrow { x, y}^d$ for arbitrary $x, y in mathbb{R}$. We prove that arbitrary trees can be realized with high probability when $d = Omega(n log n)$. We prove an analogous result for graphs parametrized by the arboricity: specifically, we show that an arbitrary graph $G$ with arboricity $a$ can be realized with high probability when $d = Omega(n a^2 log n)$. Additionally, if $r$ is the minimum effective resistance of the edges, $G$ can be realized with high probability when $d=Omegaleft((n/r^2)log nright)$. Next, we show that it is necessary to have $d geq binom{n}{2}/6$ to realize random graphs, or $d geq n/2$ to realize random spanning trees of the complete graph. This is true even if we permit an arbitrary embedding $f : V rightarrow { x, y}^d$ for any $x, y in mathbb{R}$ or negative weights. Along the way, we prove a probabilistic analog of Radons theorem for convex sets in ${0,1}^d$. Our tree-realization result can complement existing results on statistical inference for gene expression data which involves realizing a tree, such as [GJP15].
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