6
votes
Accepted
Why an eigenvector might be reasonable notion of centrality
Let the adjacency matrix of our network be $A∈\{0,1\}^{n×n}$ with an empty diagonal ($A_{ii} = 0 ∀i$).
Direct approach
Let’s start with the approach that a node’s centrality ($C_i$) shall be ...
- 186
4
votes
Accepted
Clustering Multiple Networks
Your question is not clear in a way there are two different Graph Clustering problems. One is having a dataset of different graphs and you would like to cluster similar graphs (in this case each ...
- 6,712
3
votes
Accepted
Twitter Retweet Network Visualization
For answering questions from graph, you should not visualize it. Visualizing graphs is for sake of having an overview on how it looks like in general. There are Graph Visualization techniques that ...
- 6,712
3
votes
Why an eigenvector might be reasonable notion of centrality
Let's define the centrality of a vertex as proportional to the sum of its neighbors' centralities. If you write it out and incorporate the adjacency matrix, the eigendecomposition emerges immediately ...
- 10.5k
3
votes
Accepted
Name of this type of cross variable interaction Plot
Here is python code to make a pretty good match for your picture.
...
- 303
3
votes
Is there a metric for "cliquiness" for social graphs?
The formal definition of a clique is a fully connected subgraph (or cliquiness=1.0 in your example) where the shortest path between all the nodes in the clique is 1. To relax that, you have use the n-...
- 41
2
votes
Why do we do citation analysis?
One simple example of an application of citation analysis is ranking. Imagine you do a keyword search over a collection of scientific articles, How do you rank the result set from most relevant to ...
- 2,226
2
votes
In a directed graph, how to measure whether a node is more "upstream" or "downstream"?
Please clarify what you are looking for in the presence of cycles. I'd assume the cycles aren't standalone- any node in a cycle could also have inputs from further upstream, and could also send ...
- 181
2
votes
How do I calculate for each person in the network how many people agree with their opinion?
As a fast answer, you can represent each student as a vector with $K$ elements (where $K$ is the number of topics) and values $\{+1, 0, -1\}$, denoting positive/non-existent/negative opinion about ...
- 596
2
votes
On Creating an Interoperable Network Matrix
There is no single universally accept standard, however, many packages use edgelist for sparse (un)directed (un)weighted graphs. Regarding storing and sharing, I usually see compressed text files (in ...
- 21
2
votes
Building a Citation Network to Analyze in R
I don't understand if you want to build a network of authors who cite each other, or a network of papers who cite other papers (which would be a much sparser network because the coauthorship ...
- 612
2
votes
Accepted
Protein interaction prediction- how to input this data structure
https://en.wikipedia.org/wiki/Adjacency_matrix
For such problems, you can tabulate these connections as adjacency matrix and create a network to predict weights for the matrix given some properties ...
- 2,269
2
votes
Are social network analysis and graph analytics the same thing?
No, social network analysis and graph analytics are not the same things.
Graph analytics are a general set of tools to understand graph structure (e.g., nodes and edges). Social network analysis is ...
- 22.3k
2
votes
Reduce size of a network graph for bipartite projection
I think the problem is not with the data size, but with the presence of large degree nodes (the degree of a node is its number of neighbours).
Indeed all neighbours of a node in the bipartite graph ...
- 131
2
votes
Method or tool to simulate weighted graphs with a specified weighted degree sequence
Nice question.
A natural formalization is as follows. We have a fixed weight vector $b$ (where $b_i$ corresponds to the weighted degree of vertex $i$, that is, the sum of weights of edges incident to ...
- 1,262
2
votes
What are good Bipartite Graphs Algorithms?
I can see it as: you want all the edges of graph $G$ while taking the $S \subset G=(V,E)$. For your problem this $S$ is an induced subgraph and the problem you are talking about relates to induced ...
- 21
1
vote
Accepted
How to retrieve Twitter username with UUID
It is not possible with the current version of the dataset, the User.txt ids are hashed. But, the pre-processed features are in ...
1
vote
How to do hidden variable learning in Bayesian Network with Python?
While this model could be implementable in the libpgm library (it seems to have quite rigid interface tailored to several special models, though), it will not allow ...
- 216
1
vote
Voting patterns similarities
The politicians and Political parties follow a set of principles and characteristics. They always follow these things during voting on legislations and bills. you can use T-distributed Stochastic ...
- 21
1
vote
Building a Citation Network to Analyze in R
If I understand it correctly, the matrix which was shown(snapshot) was actually generated manually. I'm I correct?, If yes, then the process which you have done is right. For generating the Graphs/...
- 2,392
1
vote
Building a Citation Network to Analyze in R
Parse an edgelist out of your data, load it into a dataframe with two columns (source, target), then feed that to igraph::graph_from_data_frame
- 3,288
1
vote
Identify social users using graph embeddings
This question can have many ways to answer but here is what I think:
Lets assume the example of very common, facebook.
Very naive sense
Number of friends is equal to the 'social-ness' of the person....
- 1,292
1
vote
Accepted
Visualizing community composition using network of pie charts
Layout algorithms in tools like networkx, igraph, and gephi will associate coordinates with your nodes which you should be able to access fairly easily. Once you have those coordinates, you just need ...
- 3,288
1
vote
Can we apply community detection algorithms for word vector space?
"Improving Community Detection in in Wikipedia Articles using Semantic Features"
This paper talks about various methods of community detection and might be helpful.
- 1,292
1
vote
how can i collect data set from social networks like instagram?
I am not aware about Instagram, or if there is a ready-to-use dataset for your purposes, but in general in order to get data from (almost) any online source you should a method called "web scraping" (...
- 353
1
vote
In what data science applications has the stack exchange dump been used?
This is a Community Wiki answer, everyone is welcome to add references.
Kaggle ran a competition to predict whether a question would be closed on Stack Overflow: https://www.kaggle.com/c/predict-...
1
vote
In a directed graph, how to measure whether a node is more "upstream" or "downstream"?
I believe what you are looking are graph centrality measures. The Betweenness centrality for each vertex reflects the ratio of shortest paths going through that vertex:
$g(v)=\sum _{{s\neq v\neq t}}{\...
- 481
1
vote
Can I use sentiment analysis techniques and text processing for detection social bot in online social networks?
Yes, because it has been done before:
http://dl.acm.org/citation.cfm?id=2808779
- 1,663
1
vote
Weighted degree in Multidimensional networks
I think your weight function should depend on $d$ as well.
The contribution from a single dimension is just the sum of incoming weights. Even for simple graphs this does not seem to have a standard ...
- 1,262
1
vote
How to get Real life Social Network Data?
Take a look at these links:
https://opendata.stackexchange.com/questions/1670/any-cdr-call-data-record-dataset
https://stackoverflow.com/questions/26229570/dataset-needed-for-cdr-analysis
http://...
- 161
Only top scored, non community-wiki answers of a minimum length are eligible