Questions tagged [networks]
Refers to network theory as part of the graph theory. For questions about neural networks, use our [neural-networks] tag.
-2
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0answers
20 views
Network security [on hold]
Q 1. The security of RSA encryption approach relies mainly on the difficulty of the prime factorization of large integer and the difficulty of calculating the Euler Totient function of large integers. ...
1
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2answers
41 views
Missing values in a variable depending on the values of another variable
I'm working on a public procurement dataset where I have information on all the participants that presented offers in 358 tenders. I'm analysing relationships between all the companies of the dataset (...
1
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1answer
18 views
representative nodes in modular network
I want to find the most representative nodes in each module in a modular network. I have used the Louvain algorithm on my graph and found two main modules. Now I want to know what nodes are the most ...
0
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0answers
11 views
Inclusion of AIC statistic in QAP netlogit regression output
I am using the netlogit function of sna for a QAP regression. The output looks something like the table below. You will see that ...
1
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1answer
22 views
“Multi-level” social network analysis?
I am very new to social network analysis and working on a project here that I am not sure what's possible to model.
I don't want to quite call this multi-level because I am not exactly looking at ...
0
votes
1answer
13 views
Finding the effect of nodes on a density heatmap
Let's say I have a geo-tagged dataset of all payment transactions for businesses in a city. I know whether each payment is made by cash or card, and have made a heatmap of where in the city the ...
0
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0answers
6 views
Picking the two most distant classes
I have a big multi-label dataset which consist of thousands of classes. I would like to find the best way to choose the two most distant classes, i.e. classes that not only never co-exist but also are ...
1
vote
1answer
23 views
How to obtain the statistical significance of a given community structure for a directed network?
So, I have several directed (multi-edged) networks, and within them each node has been assigned to one of seven categories (based on some a priori circumstances). Each category should have a higher ...
0
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0answers
19 views
Visual representation of strong associations of two categorical variables
I have a dataset of one categoric variable "supermarket" for each individual person and multiple "product" categories per person and supermarket.
E.g.:
Person 1 went shopping in supermarket X and ...
0
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1answer
40 views
Which regression used for normalized count data
I am working with social network data. I have multiple networks of various sizes and I'm calculating indegree (the number of connections between people) in each of the networks. I've been told to ...
0
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0answers
25 views
Why does a minimum value cutoff in edge values create this shape in the log-log plot of the edge values aggregated to start nodes?
I have a weighted network dataset that looks like this:
The prev and curr values contain webpages, and n is the number of times users went from the prev webpage to curr webpage. So, each data row is ...
0
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0answers
21 views
Visualising a networkx graph with vosviewer
I am trying to export a networkx graph into a format that vosviewer can read. When I wrote my graph to gml and pajek via nx.write_gml(G, path) and nx.write_pajek(G, path), vosviewer did not accept the ...
0
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0answers
15 views
Combining centrality into one based on same data type
I'm working on a project that involves count data (specifically number of interactions) from multiple different districts in a specific area. Our team has been talking about calculating a few ...
0
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1answer
18 views
Determining the closeness of nodes by their neighbours
Background
I have a directional network that is comprised of two types of nodes, business_sector nodes, and event_type nodes. ...
0
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0answers
17 views
How does Kamada & Kawai Force Directed layout algorithm interpret negative edge weights?
In Cytoscape, the Kamada & Kawai Force Directed layout algorithm is able to take negative weights between edges. Does anyone know how it's actually using the sign of these? Is it forcing ...
-1
votes
1answer
32 views
How to cluster a (directional) dissimilarity matrix with both positive and negative values?
I may be thinking of this incorrectly but what would be the best way to cluster a dissimilarity measure that has direction?
For example, if someone had condition A ...
0
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0answers
19 views
Predict node attribute from network variables
ERGM models the probability of a tie forming in a network. Is there a way of using ERGM, or an equivalent model, where the response variable is an attribute of the node, not a tie? Basically, turning ...
0
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0answers
15 views
How to interpret networks with multiple states (e.g. timeseries, conditions, etc.) that have same node set?
Apologies if this is too general but I have been thinking about it all weekend and wasn't sure how to move forward with the idea.
Here are the types of networks I am dealing with below:
I have 2 ...
0
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0answers
78 views
Compare the degree distribution of a real networks and multiple random networks
Before the paper real world networks are rarely scale free, studies used to (still do) check for the slope in degree distribution graphs and if the slope fell between 2 and 3, discern that the network ...
2
votes
1answer
22 views
shortest path optimization for multiple edge attributes
Say I have a network. The edges each have two attributes: age and height. How might I run a shortest path algorithm that optimizes on both age and height? And could I weight it so that it optimizes 0....
0
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0answers
18 views
Compare treatment effects across Levels of aggregation
Suppose I am running an experiment to see if a treatment changes the mean weight of a group of people. Note that I am specifically interested in the mean weight: if half the people get heavier, and ...
1
vote
1answer
127 views
Centrality of a directed network with edge weights - Gephi
I have the following network of court judgments in the form of a big network.(50k+ nodes and 100k+ edges with weight values). The size is the number of citations. The idea is that court judgments work ...
0
votes
1answer
232 views
Assortativity coefficient in igraph
In the context of Social Network Analysis, I want to compute the homogeneity of different networks for specific attributes. For this case the igraph package contains the method assortativity() to ...
0
votes
1answer
41 views
what's the theory foundation of the giant component strategy?
could anyone plz let me know what's the theoretical foundation of the giant component strategy?
I have used this technique to get the giant components of a not fully connected graph but i need the ...
1
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1answer
139 views
Computation of Network Homophily / Heterogeneity
I am quite confused about the calculation of network homophily in network analysis. Right now I am computing the homophily using the following function, which has been written and also described by ...
0
votes
0answers
22 views
Investigating the change of a network / factorial structure over time
I have several variables (questions from a questionnaire) that regroup into several factors (using factor analysis). However, I would be interested in knowing how this factorial structure changes ...
1
vote
0answers
26 views
Community detection in a subgraph
I find myself in possession of a bipartite weighted graph $G=(V,E)$. Let $A,B$ be the partition of $V$, so that if $i\sim j\in E$ then either $i\in A,j\in B$ or $j\in A,i\in B$.
I am interested in ...
2
votes
0answers
32 views
How to measure “cyclicity” of a directed weighted graph?
Say you have a weighted directed graph with (potentially) some cycles in it. You want to have some sort of a measure of how "cyclical" this graph is. The requirements are:
This measure C=0 on an ...
0
votes
1answer
22 views
How to Cluster Hierarchical Network Data
I have thousands of "small" networks that are strictly hierarchical in nature. Here is an example (some are much deeper, much wider etc) but this is the strict structure:
How can one cluster (e.g. k-...
0
votes
1answer
101 views
Bayesian Network: Calculate probabillity of child node given all probabillity tables
I have a Question about Bayesian Networks.
I have a network with many parent nodes and one child node.
I have the probabilities for the parents and for the child.
The child node is binary, so there ...
2
votes
1answer
33 views
degrees of freedom for t-statistic comparing two networks
I'm reading the following paper on non-parametric standard errors and tests for network statistics - https://www.stats.ox.ac.uk/~snijders/Snijders_Borgatti.pdf by Snijders & Borgatti.
When ...
1
vote
0answers
56 views
Quantifying information loss between a graph and a hypergraph
In some of the literature relating to hypergraph applications, there is an argument about information loss when representing data as a graph compared to a hypergraph.
For example, the well known ...
0
votes
0answers
76 views
Latentnet and ERGM packages in R — How to best design input networks in order to simulate networks with Homophily and Clustering?
In the ergm and latentnet packages, they allow us to input a network and specify covariates. Then, we can add in effects like ...
0
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0answers
18 views
Modelling product purchase history as a random walk in n-space
I have a large dataset of customers making monthly purchases of multiple products. Customers usually purchase between 3 and 10 products, from a large product list (1000s). I'm interested in clustering ...
0
votes
1answer
23 views
Difference between $2^{nd}$ order random walk and personalized pagerank
I've been recently working with graph sampling, and I can't seem to find useful explanation of the following two aspects. On one side there are pagerank-based algorithms, which converge to a ...
1
vote
1answer
59 views
How to generate networks of a certain density?
How can you generate small world or scale-free networks with a certain density, say .3?
In the case of random networks it seems easy because an edge is drawn based ...
0
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0answers
38 views
Connectivity vs. density for random, small world and scale-free networks
I am trying to understand a paper by reconstructing the the analyses discussed in the Validation study section, however, I am confused when it comes to how a network metric is used. Specifically, the ...
1
vote
0answers
106 views
Network modularity for exactly two communities
I have a number of empirical networks that tend to show bipolarization patterns, meaning that there are precisely two communities. In some networks, the two communities are very clearly separated (...
0
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0answers
23 views
Similarities between two networks
I am studying the similarities and differences between two research areas in terms of their descriptors (key words). I have two corpus corresponding to documents derived from both research areas. By ...
1
vote
1answer
49 views
Log-log plot comparison between a random and real world networks
I know that random networks have a bell curve (Poisson distribution) in their degree distribution and scale free networks have a straight line in their log-log plots. However, how do the log-log plots ...
1
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0answers
163 views
How to implement weighted centrality in NetworkX
I am using the following code to try implement eigen-vector centrality for a weighted graph G. The nodes represent search terms and the is an edge from node A to node B if someone searches for A and ...
2
votes
1answer
354 views
Monte Carlo or Bootstrapping for network in R
I have a large network for which I'm using iGraph in R to handle.
However, I would like to take some small random samples of that network, and calculate for example the standard deviation of parallel ...
1
vote
0answers
140 views
Interpretation of Modularity in R
I used modularity maximization cluster method to make 3 different clusters (4, 5 and 6 clusters) from a network using "Igraph" in R. I found the modularity of the three networks are 0.15, 0.23, and 0....
1
vote
0answers
50 views
Transforming dissimilarity matrix for use as weights in network
I'm trying to identify communities or clusters in a network by optimizing the modularity function. The network is a fully connected network, with undirected edges that have weights based on a pairwise ...
4
votes
1answer
425 views
Clustering network usign modularity maximization algorithm
I have been working on a Network-based clustering approach. I used "cluster_optimal" of 'igraph' package in R for clustering. The function works by modularity maximization algorithm. I have ...
2
votes
0answers
170 views
Random Forest for financial networks modelling
One of the hottest topics in today econometrics is financial networks models where researches use vector autoregressive (VAR) models applied to time series of daily volatility measurements of ...
1
vote
0answers
43 views
Graph Theory / Network Analysis - properties variation
I have a rather complex network (air travel in the US) with more than 500 nodes, and small-world, scale-free proprieties, spanning over 10 years, and with quarterly information.
As I'm trying to ...
2
votes
1answer
41 views
To test for small-world property, does the random graph generated has to be completely connected?
For a small world property, the ratio of the average path length and the mean path length of random networks has to be close to one.
My question is: When generating a random graph using the Erdős-...
4
votes
1answer
54 views
Statistical test to identify enriched edges in a network
I have a network with N nodes and E directed edges. Each edge (Eij) is an integer that represents the number of connections between a source node (Ni) and a target node (Nj).
My null model is that ...
0
votes
1answer
40 views
What are some common properties usually associated with undirected complex networks?
I am aware of the "scale free", "existence of community structure" and"small world" phenomena that commonly occur in real world networks, but what are some other properties associated with these kinds ...
