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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22 views

Identify individual networks within dataset containing many (using SAS preferably)

I have a dataset of links/edges that looks something like the following (except significantly larger - approx. 50,000 links): ...
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Estimating a network-like structure with lead/lag relations

This is a very general question, but any ideas or hints towards the right direction would be very helpful. Assume a dataset with a number of countries $i = 1, \ldots, N$ and a set of indicators $X \in ...
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1answer
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What is the difference between local efficiency and betweenness centrality in network analysis?

There are many network properties that you can extract for a given node. Two I have encountered that sound conceptually very similar to me and that I have difficulty distinguishing are betweenness ...
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15 views

Similarity matrix for directed graph vs. undirected graph producing odd/disparate numbers on diagonal (i.e. self-similarity)

In a correlation, distance, or similarity matrix, comparisons to self should be along the diagonal as a constant 1 or 0. However, I have found that while similarity to self is a constant 0 in ...
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8 views

Accounting for connectedness during the analysis of nodes in a directed acyclcic graph

I am studying a river network and environmental features measured at different stations along the network. Often, one station is higher up the river than another (or multiple others). I can ...
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1answer
47 views

What are the conditions for a graph's adjacency matrix to not have a negative eigenvalue with magnitude>=1?

Say I have a (directed) graph $G$ with an adjacency matrix $A$. For the sake of the question, let's assume it's normalized column-wise (edge weights are normalized so the sum of out-edge weights per ...
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4 views

implementation of network autocorrelation models

I've googled this but can't find an answer: where can I find a good implementation of a network autocorrelation model. I want to predict a dichotomous response variable from a network independent ...
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21 views

Hierarchical graph clustering using a kernel matrix in R

I have a set of 9 directed graphs of differing sizes and I'd like to use graph clustering to create a dendrogram illustrating their structural similarity, similar to what's done in the NetConfer ...
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8 views

degree centrality for two clusters in the network to identify most central influencers “unique” to each cluster

I have a network containing 2 groups of people A and B (taken from twitter). I want to find the most influential people within each group but I want to make sure that these people are specific to ...
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9 views

Grouping nodes together that have no connection

We have a data set of 200 people and how much they have interacted with each other based on email metadata (collaboration hours = edge weight). We were asked to put people into 20 groups of 10 so that ...
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Edge weights as dependent variable in a network / dyadic data

Let's say that I have a network of countries that export to each other (directed edges: A to B, B to C, but not B to A). Countries (vertices) have attributes, like their Human Development Index score, ...
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Methods to align/reduce distance between two or more 3D graph-spaces?

I'm trying to align multiple graphs of spatial data, similar to image registration, but on a 3D graphspace of a select feature. I have a bunch of point data with x,y,z coordinates that together, ...
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How can I compare interaction network's metrics from two samples?

I'm constructing interaction networks with bee-plant interaction data, using bipartite R package. I want to compare these interactions between two different seasons. In some papers they use a t-test, ...
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What network layout or clustering algorithms can handle a mix of negative and positive weights?

In particular, I would like to create a network from correlation data. The negative values should represent repulsive forces and positive values as attractive forces. Values close to 0 for weights ...
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Output for ERGM (Exponential Random Graph Model) is not correct

I really need some advice regarding running an exponential random graph model (ERGM) in R. These are the two social networks that I am using. First social network: Second Social Network: Now, this ...
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2answers
75 views

How do I evaluate correlation, that appears non-linear

Directed here from StackOverflow Let's say I want to assess if there is a correlation between two fields, one of which I know to have a power distribution. A lot of the information I read assumes ...
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Is a grid-like network more efficient than a random network?

Imagine two different types of street networks with the same number of nodes and where edges are weighted according to their length. Both network types cover the same geographic area (say 1km²) and ...
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binwidths/no. of bins when overlaying two histograms

Should the binwidths for two histograms be same or no. of bins in both histograms be same when they are overlayed for comparison? or there is no correlation? I am comparing histogram of centrality for ...
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Recommending without knowing the clusters

I've heard of some methods to produce recommendations based on clustering: if many of the users who enjoy A also enjoy B, and you enjoy A, then you are likely to enjoy B. A and B in this case form a "...
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18 views

Binwidths/no. of bins for 2 histograms for overlaying them

Should the binwidths for two histograms be same or no. of bins in both histograms be same when they are overlayed for comparison? or there is no correlation? I am comparing histogram of centrality for ...
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18 views

Data Fusion Algorithms for Network or Graph Data

Let's suppose we have two distributions defined over graphs, $P_1(G)$, $P_2(G)$. For example, these could correspond to familiar distributions like Erdős–Rényi, Barabási–Albert, or Watts–Strogatz, or ...
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1answer
9 views

Network linkage formation prediction

Is there a statistical model that can study determinants of network linkage formation? For a set of companies (where we observe their industry, annual revenue, etc), we see which pairs are connected ...
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1answer
48 views

Degree and weight preserving randomisation in networks

I have a network in which nodes are highly interconnected (250 nodes where 90% of the nodes have degree = 249). The connections are weighted with a normalised index that goes from 0 to 1, where 1 ...
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1answer
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How can I encode a network into a machine learning feature?

I am developing a predictive machine learning model. The dataset is social media posts from Twitter relating to a particular topic. One of the features I would like to incorporate into the model is ...
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Intuition behind null model for disparity filter algorithm

I'm trying to better understand the disparity filter algorithm for weighted networks: Original paper: https://www.pnas.org/content/106/16/6483 Wikipedia link: https://en.wikipedia.org/wiki/...
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1answer
34 views

ERGM with larger log-likelihood but worse fit than reference model?

I'm using the R package statnet to fit some ERGMs to the Faux Dixon High simulated network data provided with the package. The first model I fit is almost identical ...
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what is the probability that a randomly chosen vertex belong to a small component of size S?

I was reading chapter 12 of "Networks: An Introduction Book by Mark Newman" about Random Graph. part 12.6 of the book is about the small components in Random Graph. page 405 equation 12.24 and 12.25 I ...
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What is constraint and effectivesize in structural holes?

Today, I spent the whole day trying to understand what structural holes in network means. More specifically I want to clarify what the two measurements constraint and effective size means? Is it good ...
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0answers
25 views

Why is my correlation matrix dropping that many NA?

I am trying to build a correlation matrix among documents per topic on a Latent Dirichlet Allocation model by text2vec, getting a doc_topic_distr matrix like below, with only first 5 documents, it's a ...
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43 views

Compare networks, including centrality measures, clustering/community detection results

Hi my fellow researchers, I am trying to compare two networks based on exactly same group of individuals (179 unique individuals): One network is based on these individuals' meeting data (two-mode/...
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What is the difference between node clustering and network community detection?

Node clustering algorithms in which we attempt to determine dense regions of the graph based on edge behaviour(either be a distance value or a similarity value). The more similar nodes come together ...
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1answer
124 views

Network analysis: Formal definition of the number of 1st order neighbours of degree 1

I am looking for a formal definition of a network metric I am using in a scientific article. Let $i$ be a vertex in a graph $G$ and $N(i)$ are the first order neighbors of vertex $i$. I am interested ...
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1answer
91 views

Calculating the Expected life of network with hazard functions

I have been asked to solve some questions in the statistical program R. First, I want to find the expected life length (by numeric integration) of a network with 3 parallel components (T1,T2,T3) and ...
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114 views

How can I visualize and cluster weighted graphs in python?

On any ecommerce website, you have options to apply filters to filter out products. For example: So I have data of how many users applied what filters tuples on the website. Which is fetched from ...
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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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22 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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0answers
37 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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0answers
37 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
123 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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2answers
46 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
45 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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1answer
53 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
23 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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1answer
44 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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27 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
120 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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1answer
21 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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2answers
114 views

Order of Conditional Independence Tests

I'm studying the PC algorithm for learning the structure of a Bayesian Network. One of the steps refers to performing several rounds of conditional independence tests of increasing order, zero, first,...
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1answer
305 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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1answer
53 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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