We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from an m-dimensional metric space with power-law distributed influence regions best fits samples from real-world networks when m scales logarithmically with the number of nodes of the network. This supports a logarithmic dimension hypothesis, and we provide evidence with two different social networks, Facebook and LinkedIn. Further, we employ two different methods for confirming the hypothesis: the first uses the distribution of motif counts, and the second exploits the eigenvalue distribution
In online communications, patterns of conduct of individual actors and use of emotions in the proces...
A number of recent studies have focused on the structure, function, and evolution of on-line social ...
This is an examination of a set of dimensional conceptions of graphs that might be used to shed ligh...
<div><p>We consider the dimensionality of social networks, and develop experiments aimed at predicti...
We consider the dimensionality of social networks, and develop experiments aimed at predicting that ...
We study the link structure of on-line social networks (OSNs), and introduce a new model for such ne...
Social networks can be embedded in an n-dimensional space, where the dimensions may reveal or denote...
Social networks are in general dynamically due to the involvement of many people on the web such as ...
<p>The specific dimensional scaling lines fit to the data in <a href="http://www.plosone.org/article...
<p>The MGEO-P model correctly captures the peak of the distribution around 1, but fails to completel...
We perform here a comparative study on the behaviour of real and synthetic social networks with resp...
We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test w...
Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal n...
Although the structural properties of online social networks have attracted much attention, the prop...
This thesis explores three practically important problems related to social networks and proposes so...
In online communications, patterns of conduct of individual actors and use of emotions in the proces...
A number of recent studies have focused on the structure, function, and evolution of on-line social ...
This is an examination of a set of dimensional conceptions of graphs that might be used to shed ligh...
<div><p>We consider the dimensionality of social networks, and develop experiments aimed at predicti...
We consider the dimensionality of social networks, and develop experiments aimed at predicting that ...
We study the link structure of on-line social networks (OSNs), and introduce a new model for such ne...
Social networks can be embedded in an n-dimensional space, where the dimensions may reveal or denote...
Social networks are in general dynamically due to the involvement of many people on the web such as ...
<p>The specific dimensional scaling lines fit to the data in <a href="http://www.plosone.org/article...
<p>The MGEO-P model correctly captures the peak of the distribution around 1, but fails to completel...
We perform here a comparative study on the behaviour of real and synthetic social networks with resp...
We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test w...
Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal n...
Although the structural properties of online social networks have attracted much attention, the prop...
This thesis explores three practically important problems related to social networks and proposes so...
In online communications, patterns of conduct of individual actors and use of emotions in the proces...
A number of recent studies have focused on the structure, function, and evolution of on-line social ...
This is an examination of a set of dimensional conceptions of graphs that might be used to shed ligh...