Linkage (version 0.9)

linkage.post: Post a job on Linkage.fr to cluster a network with STBM

Description

Post a clustering job on the server Linkage.fr though the API. The Linkage.fr server implements the Stochastic Topic Block Model (STBM, Bouveyron et al., 2018, doi:10.1007/s11222-016-9713-7).

The users should have registered on the web server https://linkage.fr. Registration is free of charge for individual and academic users.

Usage

linkage.post(file, token, job_title = "", clusters_min = 2, clusters_max = 10,
              topics_min = 2, topics_max = 10, filter_largest_subgraph = TRUE)

Arguments

file

the location on the disk of the CSV file containing the communication network. Each line of tje CSV file should be of the form: sender_id, receiver_id, text of the message.

token

The token of the user. This personal token can be found on https://linkage.fr/developers/ after registration. Registration is free of charge for individual and academic users.

job_title

Title of the job

clusters_min

Minimum number of node clusters to test

clusters_max

Maximum number of node clusters to test

topics_min

Minimum number of topics to test

topics_max

Maximum number of topics to test

filter_largest_subgraph

a boolean indicating if the clustering should be done only on the largest subgraph or not

Value

The id of the job is returned.

References

C. Bouveyron, P. Latouche and R. Zreik, The Stochastic Topic Block Model for the Clustering of Networks with Textual Edges, Statistics and Computing, vol. 28(1), pp. 11-31, 2017 <doi:10.1007/s11222-016-9713-7>

Examples

# NOT RUN {
data(Enron)
write.table(Enron, file="Enron.csv",row.names=FALSE,col.names=FALSE, sep=",")
file = "Enron.csv"

# Provide the user token, which is provided on "developers" page
# of http://linkage.fr (after registration)
token = "xxxxxxxxxxxxxxxxxxxx"

# Post the job
job_id = linkage.post(file, token, job_title="My job: Enron",
                      clusters_min = 8, clusters_max = 8,
                      topics_min = 6,topics_max = 6,
                      filter_largest_subgraph = TRUE)

# Monitor achievment of the current job
ans = linkage.check(token)

# Retrieve results (once achievment is 100<!-- %) -->
res = linkage.getresults(job_id,token)

# Plot the results
plot(res,type='all')
# }