Questions tagged [networks]
Refers to network theory as part of the graph theory. For questions about neural networks, use our [neural-networks] tag.
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Stochastic blockmodel with continuous weights in [0,1]
I want to use a stochastic blockmodel (SBM) to cluster the nodes in a network where the edge weights are continuous numbers between 0 and 1. It seems that R-packages such as ...
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Bibliometric & Co-occurrence Analysis
I am very new to network analysis and bibliometrics. So excuse for my silly & basic question.
I am interested to find how Journals (academic) are related to one another. Each journals have their ...
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What methods to use for statistical analysis of a network structure?
I have a network structure (adjacency matrix) and want to find a method that tells me which features of my network are most important to explain my response variable. In this case its an infection ...
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Quantifying (observed) spatial clustering?
I am looking for some advice regarding spatial statistics.
I have a large dataset with multiple samples across 5 different conditions. Each sample is composed of different point types in 2D space. For ...
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When are we required to add isolates as part of the ergm model and how to interpretate the coefficient
Recently, I am trying to perform network analysis by modeling a network of companies with ERGM. When i was looking into some popular terms to be added in the model, I come across with isolates term, ...
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Utilizing bipartite network information in standard regression analysis
The gist of my somewhat general question is if there are some useful approaches to utilize information about relationships between individuals embedded in a bipartite network when the goal is a node-...
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Detrending Time Series Data for Network Analysis
In order to run psychometric network analyses on (up to) 10 repeated measures for 13 variables in R, I need to detrend my 13 variables (B1 to B13) first. My problem is that not all subjects (id) have ...
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Community detection (graph clustering) vs. distance matrix clustering
I need to cluster objects.
Each object is described by the set of features, each of which is either '0' or '1'.
'1' means that object has this feature.
'0' means that there is no information that ...
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12
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Regression model on edge list
I would like to fit a regression in which my data is links (edges) from the network and the output is weight of each link.
Income level is a node attribute and for each link two nodes are involved, so ...
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Nonsignificant individual level paths in GIMME network model output
I used the R package gimme to create individual level network models using repeated measures data from each person in a 95 person sample.
The code ran successfully, ...
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Does the weighted Louvain algorithm for maximizing Modularity result in one of the modules containing low weight edges for a fully connected network?
I currently have an implementation of the Louvain Algorithm from the Brain Connectivity Toolbox (BCT) written by Rubinov and Sporns 2010. I was discussing the implementation of it with a professor who ...
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How can I calculate the sample size in this multivariate problem?
I have two data sets containing scores of a test applied to two groups of people: A control group (neurotypical individuals) and a group of people with a specific neurological condition. The aim is to ...
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How to perform random walk on multilayer network to predict new edges
I have a multi-layer network that is a union of 3 networks (field of human biology/ Omics data). The 3 networks have dense connections within each other (local), however sparse connections to each ...
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How to statistically test an increase?
I have two temporal networks in which I report their number of nodes and the average degree in different time intervals:
time
Nodes_Network_1
Nodes_Network_2
Average_degree_Network_1
...
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Compare Eigenvector Centrality of two networks
We have two networks (G1, G2), one with 4 times more nodes than the other, and we want to compare the eigenvector centrality of their three most central nodes (e.g. top_1 node of G1 vs top_1 node of ...
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PageRank denotes how many inputs a node has from influential nodes (directed form of eigenvector). Is there a metric for outputs to influential nodes?
PageRank is the directed form of eigenvector centrality, denoting how influential a node is in terms of indegree edges. Is there an outdegree version?
PageRank assumes that “ important nodes are those ...
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How to study what moderates a correlation?
I'd like to illustrate my objective with an example:
Imagine we have collected data on the height, weight, and level of sports activity (represented as either a continuous or categorical variable) ...
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Sample size estimation
I have $n$ data points that run in hundreds of millions. Ideally, I want to connect them with each other (based on a condition), run random walks on this interaction network, and make some inferences ...
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How to deal with participants recruited twice in a RDS (repondent-driven sampling) study?
I have RDS data and identified participants recruited twice during the study. How should I handle these duplicates? If I delete the second recruitment, it will disrupt the network. Can I consider the ...
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Probability that two vertices are connected
I'm reading:
Clauset, A., Newman, M.E.J., Moore, C., 2004. Finding community structure in very large networks. Phys. Rev. E 70, 066111. https://doi.org/10.1103/PhysRevE.70.066111
There is written that ...
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igaph gives me a diameter, but I think the diameter is another one [closed]
Given this network:
...
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Calculating modularity gain of switching a node from one community to another (Louvain algorithm)
I am trying to implement the Louvain algorithm in PySpark.
An important part of the algorithm involves calculating the modularity gain of taking node $i$ out of its current community $C_0$ and placing ...
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Method for comparing 2 3-dimensional networks (igraphs in R) [closed]
I'm looking for a way to compare 2 (or more) igraph objects in R. These are trajectories in 3-dim which are a network of nodes and edges but are not necessarily the same number of either, just that ...
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Hopfield Network Energy
Can neurons in Hopfield Network have non-binary values ( continuous values instead of -1 and +1)? If they can have non-binary values , is energy expression for hopfield NN stays the same? What is the ...
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How to interpret the minimum spanning tree in a fully-connected graph?
Can someone explain how the resulting graph is the minimum spanning tree (MST) from the fully-connected undirected graph? I don't understand how this is interpreted in this context.
Definition ...
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How can I model or estimate the probability of a given network connection in a bipartite graph of relationships that may or may not exist?
I have a large set of network data, with many groups. Within each group, there are some criteria for creating "candidate" relationships between entities.
Below I have an example of 8 groups, ...
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How to handle missing data when calculating network homophily/assortativity?
I am trying to calculate network homophily/assortativity for a graph. However, some of my nodes have missing values. It turns out igraph's assortativity functions have no "na.rm" function ...
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419
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Application of Bayesian Networks to tabular data
I have been going through some tutorials regarding Bayesian Networks, but i have yet to see them applied to tabular data, i.e. a dataset. I have created this dummy example to experiment, and attempt ...
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Graph/Network Clustering Models that Use Covariate Information
I have been reading about Clustering Models on Graph/Network data.
For example, there seems to be a popular Clustering Model for Graph/Network data called Louvain Clustering (https://en.wikipedia.org/...
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Eigenvector centrality comparison
Let's say we calculate the eigenvector centrality of the same set of nodes in different years (we have a network each year). Note that the eigenvector centrality is normalized in such a way that the ...
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Does one network predict the other?
Here is my problem:
I have two undirected networks, $G1$ and $G2$ which change over time
The nodes in each network are identical
The edges are always constrained between 0 and 1
I want to know ...
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How to Cluster Several Graphs?
I'm relatively new to Graph Theory, but I'm wondering if I have a set of Graphs {G1, G2, ..., Gn}, are there any algorithms that allow for clustering these graphs? taking into account the nodes and ...
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Is in a DAG every node an ancestor or a descendant?
This is the second question that I am asking here about these note about DAGs http://www.stat.cmu.edu/~larry/=sml/DAGs.pdf .
When discussing the max-sum algorithm, they want to evaluate the marginal ...
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A network has many conflicting edges. How to create a good visualization for it?
I'm having a network of belief system. It has ~100 nodes, 316 regular edges and 78 conflicting edges. (If belief B conflicts with belief A, then node B and node A share a conflicting edge. If belief B ...
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igraph's "assortativity" function returns NaN if all attributes are identical. Why?
I am trying to use igraph's assortativity function. It returns positive values if more similar nodes have similar attributes and negative values otherwise.
Indeed, if I randomly generate attributes ...
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Normalizing ASPL and CC for Number of Nodes?
I have a bunch of human-built networks of different sizes and am trying to compare them using Small World Network metrics: Average Shortest Path Length (ASPL) and local average Clustering Coefficient (...
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Measuring the divergence in centrality statistics for similar networks?
I want to measure the similarity/divergence between the centrality of nodes in two publicly available word association networks.
In my analysis, we have a long list of nodes - 12,000 or so - and then ...
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What does it mean for Katz Centralities to "diverge"
In Mark Newman's Networks book, 2010 edition, page 173, he explains some mathematical details behind the Katz Centrality measure:
In matrix terms, Eq. (7.8) can be written x = αAx + β1, (7.9) where 1
...
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1
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Reading on "Economic nowcasting" for a probabilist
I am about to attend an interview for a postdoc in "economic nowcasting". I am work mostly in probability, particularly complex networks and random graphs.
I am looking for some good reading,...
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Symbol interpretation in non-constant power law density
I am reading Barabasi book on network science. I am struggling to interpret the density formula for a power-law degree distribution with low-degree saturation and high-degree cut-off (http://...
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How do I know if violations of assumption of sparsity is problematic?
I am running a network analysis in R using the estimateNetwork(default = "EBICglasso") function from the bootnet package. I have set ...
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How can this CDF be decreasing? (power-law)
I am reading the first vignette of the powerRlaw R package.
It uses the moby dataset, which is an array of word frequency. Each element is a word, and the value if ...
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Network analysis: density of communities/partitions (and other metrics)
After running a community detection algorhythm (e.g. edge betweenness, or greedy modularity), I like know the density of each seperate community, and potentially some other metrics, too.
My desired ...
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what would a network looks like if the modularity is almost -1?
I know that larger positive modularity is good, and often lies between -0.5 and 1. But what would the network looks like if the modularity is appoaching -1? For example, equals to -0.7?
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Constructing a Weighted Random Graph
I want to create a weighted random graph (in contrast to the unweighted Erdős–Rényi model). I have a list of weights (derived from a real-world network, very skewed distribution that most weights are ...
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Model Comparison for Weighted Network
I have a weighted network data and I want to know whether this network possesses small-world features or the features of a scale-free network.
I know for unweighted networks, I can create comparable ...
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Is Kendall's tau adequate to test for a non-monotonic relationship?
Goal
Networks can have so many nodes that it's hard to study them. That is why in some cases nodes are clustered together. I am looking at whether the betweenness of a node is maintained after the ...
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How can I perform a meta-analysis on Kendall's tau?
Goal
Networks can have so many nodes that it's hard to study them.
That is why in some cases nodes are clustered together.
I am looking at whether the betweenness of a node similar to the one of its ...
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1
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1
answer
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Given a graph, test if some vertices are more connected than the background
I have a neighborhood graph of some 10k vertices (a k-NN graph of single-cell RNA-seq data).
I am interested if a given set of vertices is more connected to each other than you would expect by chance. ...
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Network clustering stability using bootstrapping techniques
I use the standard modularity-maximisation Louvain clustering method to partition a large undirected network into communities. I fear the result of the partition is quite fragile.
Is there a standard ...
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