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Questions tagged [networks]

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Refers to network theory as part of the graph theory. For questions about neural networks, use our [neural-networks] tag.

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19 views

Regression with autocorrelation given by a graph

Supppose I would like to fit a standard regression model of the form $y = \alpha + X \beta + \epsilon$, but my observations come from a networked population (eg. social network). I have the graph $G$ ...
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21 views

Help wrapping my head around an analysis based on social networks

I should preface this with a slight disclaimer. The scenario I have outlined is not actually the data I am working with, it is an analogy that I have created (hopefully accounting for all important ...
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15 views

Summary statistics for bipartite networks

I have a large bipartite network that I would like to summarise. So far, I have found the following summary statistics: Degree centrality Graph density Modularity Nestedness I have not found a ...
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26 views

Reference request: Network/graph topology inference

I am a mathematician looking for a survey/book on methods for inference of graph/network topology (structure). Specifically, the kind of problem I am looking to study is as follows: Given a graph $...
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1answer
33 views

Network analysis - Correlation is positive and significant, but coefficient of simple logistic regression is not significant?

I have an adjacency matrix and another which represents whether the two nodes share an attribute. Consider it like an homophily test. We want to test if the likelihood to form a connect depends on the ...
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34 views

Review paper on causal modelling of complex networks

Although I have a growing interest in network neuroscience and complex neuroscience in general, I have quite a bit of trouble following Twitter discussions on causal modelling of brain network ...
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2answers
45 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 (...
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2answers
24 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 ...
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18 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 ...
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1answer
30 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 ...
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1answer
16 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 ...
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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 ...
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1answer
33 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 ...
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21 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 ...
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1answer
51 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 ...
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27 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 ...
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47 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 ...
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17 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 ...
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1answer
19 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. ...
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44 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 ...
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1answer
87 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 ...
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20 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 ...
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16 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 ...
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112 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 ...
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1answer
31 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....
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20 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 ...
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1answer
208 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 ...
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1answer
369 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 ...
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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 ...
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1answer
221 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 ...
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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 ...
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47 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 ...
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1answer
23 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-...
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1answer
135 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 ...
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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 ...
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63 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 ...
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1answer
46 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 ...
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1answer
73 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 ...
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43 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 ...
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132 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 (...
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1answer
60 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 ...
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209 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 ...
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1answer
378 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 ...
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162 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....
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63 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 ...
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1answer
524 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 ...
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0answers
201 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 ...
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44 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 ...
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1answer
48 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-...
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1answer
65 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 ...

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