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Questions tagged [igraph]

igraph is a collection of software packages for graph theory and network analysis. Its core is a software library written in C/C++, and it has interfaces to GNU R and Python.

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igraph - Minimum vertex set origin for destination

Part igraph question, part graph theory question. I have a digraph from a set of origin vertices (warehouses) to destination vertices (customers). A given origin vertex has edges only to a limited ...
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1answer
282 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
167 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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17 views

How to get accurate shortest paths for signed weighted graphs with negative cycles?

I work with resting state functional data and my lab supervisor prefers to use signed, weighted, partial correlation networks (it's fairly standard in rsfc analyses). An unfortunate characteristic of ...
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80 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 ...
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26 views

What are the available metrics of community structure quality in a graph?

I know that modularity can be used for evaluating the "quality" of a community structure found by an algorithm in a graph. What other options are available? I need to evaluate different algorithms ...
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57 views

Partitioning a graph based on sum of edges weights inside the groups and leading outside the groups?

Suppose I'd like to partition a graph in communities. My objective would be to find the best set of k groups where by "best" I mean the set of groups that maximizes, for each group, the sum of weights ...
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278 views

Kamada Kawai vs Fruchterman Reingold

I am trying to visualize microbial correlation networks. I am using igraph in R. And my goal is to have weighed edges based on the correlation coefficient between the nodes. I don't understand what ...
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1answer
63 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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39 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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120 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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26 views

Does recursive partition of a graph using min-cut yield the minimum cumulative sum of edges weights?

Suppose I have an undirected graph with weigthed edges a and vertices. I want to partition the graph in N subgroups. Suppose that any time a cut occurs, I sum the weights of the edges which belong to ...
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1answer
27 views

What is the state of the art process for finding isolated communities in graphs?

Is there a state of the art process to follow for finding isolated communities in graphs? I know there are a lot of algorithms available, but I struggle to find a set of steps for preprocessing and ...
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generate igraph with varying graph level centralization [closed]

How do I generate several igraphs with varying graph level centralization? I am familiar with sample_(...), that variations of 'sample_' allow me to generate graphs GIVEN a MODEL....but not given ...
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1answer
45 views

Bias correction of a sampled igraph

Suppose I have a sample (S) of a graph where S is a subset of G -- the population Graph. Is there a way (theoretical) to compute for bias in the estimation of centralization (as in igraph::...
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14 views

Why switching edges definition changes the result of random walk search for communities? (walktrap)

If a graph object is a not directed graph, then the following set of operations should yield the same result: ...
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1answer
362 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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1answer
458 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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23 views

Measure propensity of contagion between sets of nodes using r igraph

What would be a good way of measuring propensity of contagion between two sets of nodes in a network? I tried creating an index that includes path distance and number of shortest paths, but network ...
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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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223 views

Setting initial assignments for mixed-membership stochastic blockmodel

I created two networks at two points (in the middle of the month and at the end of the month). Tried to run mmsb.collapsed.gibbs.sampler for the first network and obtained network communities. However,...
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1answer
155 views

Difference between real and random graphs in bipartite networks

I am trying to prove that my network is a real network and not a random network by doing certain tests in igraph. The clustering coefficient of my network is zero, so I wont be looking at that ...
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412 views

Clustering Coefficient of zero in the Network

The clustering co-efficient of my real network is zero. As a matter of fact, all the nodes of the network have a clustering coefficient of zero. I am trying to compare my network to an ensemble of ...
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Modeling products (from sales data) in a graph network for clustering and product recommendations.

I have a high level question about whether or not graph networks would be an appropriate method to model a situation I'm studying. It's been a while since I last worked on a project building/analyzing ...
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447 views

Input to fit a power-law to degree distribution of a network

I would like to use R to test whether the degree distribution of a network behave like a power-law with scale-free property. Nonetheless, I've read diferent people ...
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1answer
308 views

Log-likelihood in fit_power_law{igraph}

The R package igraph has the fit_power_law function which, as you can imagine, can fit a ...
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2answers
465 views

R package for graph manipulation: transitive reduction and cliques

Can anyone suggest an R package for graph manipulation that can find cliques and also performs transitive reduction? From websearching I see that I can find cliques with igraph. (Transitive ...
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1answer
32 views

How to alter undirected, binary graph to have specific graph-analytical characteristics while keeping others constant

I am working on a undirected, binary graph (derived from functional neuroimaging). I would like to alter this graph to change specific graph-characteristics (e.g. a specific value for the global ...
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1answer
2k views

Calculating Transitivity (Clustering Coefficient) from Adjacency Matrix, and igraph package

Suppose $G$ is a simple, undirected graph. The corresponding adjacency matrix, $A$ is binary, symmetric, and has all zeroes on the diagonal. By definition (Networks: An Introduction, M.E.J Newman), ...
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1answer
350 views

How to compare the degree distributions of 2 different graphs

I am new to statistics.I am trying to compare 2 networks. Can anyone pls help me to understand what the degree distribution of the 2 networks say. I mean the similarities or differences bet the 2 ...
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2answers
266 views

Community detection in network

I'm fairly new to the subject of network theory and community detection, and I'm trying to apply to some data that I have. To start, my data essentially looks like this: Basically, what I have is a ...
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83 views

Network/Graph Analysis Beginner Resources

I am a beginner to Network/Graph Analysis. I have data in the following format: Customer | CustomerSpend Anna $10 Bob $30 Charlie $50 ... .....
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81 views

Social Network Analysis: Measuring the link between vertex values

I'm relatively new to social network analysis and from what I understand many of the common statistical technique do not work in social network analysis due to the non IID nature of networks. My ...
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0answers
64 views

Testing if a directed, bipartite network is non-random

I am struggling with finding a suitable approach to determine if a directed, bipartite network is non-random, i.e., if the relations between the nodes and edges of my empirical network are due to ...
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1answer
2k views

Community detection and modularity

I am reading the book "Network science" of Barabasi and in particular the chapter on community detection. If I understand correctly, modularity is a goodness factor of partition calculated by a ...
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2answers
177 views

Problems with representing and analysing non-network data as a network?

Suppose I have a dataset with 200 observations of 30 categorical variables. The dataset describes websites and different kinds of design features they deploy (or do not deploy). If I were to convert ...
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1answer
645 views

igraph shortest path export as vector [closed]

This is probably a very simple question but I cannot seem to solve it: I'm using the igraph package and want to export the vpath part of the get.shortest.paths output as a vector so that I may work ...
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1answer
83 views

Does Newman clustering work on weighted graph with non-integer weights?

I have a weighted undirected graph, where weight is distance and it is between 0 and 1. I want to apply the weighted version of Newman clustering. I think weight must refer to strength or similarity, ...
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1answer
325 views

igraph betweenness depends on order of edges

I have a question whether order of edges in graph should matter or not? It seems that betweenness function produces slightly different results for different orderings of input file. input file : ...
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119 views

EdgeRank for eCommerce product feed

I am running my eCommerce store with around 1000 products with 10 categories. I want to show these products in feeds. But there are lots of products so its very complex to define priority list for ...
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2k views

Graph clustering algorithms which consider negative weights

I have a graph instance with weighted directed edges which values can be in range [-1,1]. I need to do clustering on this graph, in order to find out groups in which vertices are more correlated. I ...
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1answer
159 views

Validating Personalized Pagerank Matrix computation in R

My question is with reference to this paper here This is an excerpt from the paper From the similarity of the two equations we can see that if ppr_alpha_u is added up it will be equal to pr_alpha ...
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1answer
400 views

Betweenness values for nodes different in SNAP and iGraph network analysis packages?

I compared results from using the SNAP (Stanford Network Analysis Project) Python library and the iGraph R library for analyzing networks. The betweenness values for nodes seem to be rather different ...
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1answer
443 views

Should I use IN or OUT degree in Network Diffusion Model of Twitter network using iGraph?

I'm trying to run Independent Cascade Model for my Twitter graph to see who I have to stimulate to get the maximum cascade. This code is inspired by http://php.scripts.psu.edu/hxc249/code_segments/...
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116 views

Is it appropriate to use feedback centrality measures with directed networks?

I am analyzing adolescent friendship networks. I am trying to identify key players using different centrality measures, but I am not sure if it is right to use feedback centrality measures (...
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94 views

Missing values with Community structure in networks?

Is there a way to predict Missing values with Community structure in networks? I have a data set with a couple dozen variables, such as age, level of education, self-assessed (via a Likert scale) ...
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129 views

Search in a graph of medical records

I have a hierarchical order of a disease list. Just for example: Respiratory system disease 1.1. Asphyxia neonatorum 1.2. Croup 1.3. Lower respiratory tract disease 1.4. Bronchial disease 1....
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1answer
1k views

techniques for sampling graphs? (possibly implemented in r packages)

Let's say I have a very large graph that proves impractical for visualization ends and I wanted to sample a random subgraph. (I know that I can filter out a subgraph via measures like degree, ...
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1answer
875 views

In R: How do 'centralization' measures of the STATNET and iGraph package handle disconnected networks?

I am working with about 300 disconnected of different sizes. I calculate different graph-level centralization measures for these networks using the STATNET and iGraph packages in R. However, I find ...
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1answer
98 views

What kind of model can I try to fit in this plot?

I have a plot like this. I wish to apply a model to this, however, I guess a linear regression model won't work on this. What I did was plot it on logarithm x and logarithm y axis as well but it ...