Coupling Analysis
It performs a coupling network analysis and plots community detection results on a bi-dimensional map (Coupling Map).
couplingMap( M, analysis = "documents", field = "CR", n = 500, label.term = NULL, ngrams = 1, impact.measure = "local", minfreq = 5, stemming = FALSE, size = 0.5, n.labels = 1, repel = TRUE )
M |
is a bibliographic dataframe. |
analysis |
is the textual attribute used to select the unit of analysis. It can be |
field |
is the textual attribute used to measure the coupling strength. It can be |
n |
is an integer. It indicates the number of units to include in the analysis. |
label.term |
is a character. It indicates which content metadata have to use for cluster labeling. It can be |
ngrams |
is an integer between 1 and 4. It indicates the type of n-gram to extract from texts.
An n-gram is a contiguous sequence of n terms. The function can extract n-grams composed by 1, 2, 3 or 4 terms. Default value is |
impact.measure |
is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources).
It can be |
minfreq |
is a integer. It indicates the minimum frequency (per thousand) of a cluster. It is a number in the range (0,1000). |
stemming |
is logical. If it is TRUE the word (from titles or abstracts) will be stemmed (using the Porter's algorithm). |
size |
is numerical. It indicates the size of the cluster circles and is a number in the range (0.01,1). |
n.labels |
is integer. It indicates how many labels associate to each cluster. Default is |
repel |
is logical. If it is TRUE ggplot uses geom_label_repel instead of geom_label. |
The analysis can be performed on three different units: documents, authors or sources and the coupling strength can be measured using the classical approach (coupled by references) or a novel approach based on unit contents (keywords or terms from titles and abstracts)
The x-axis measures the cluster centrality (by Callon's Centrality index) while the y-axis measures the cluster impact by Mean Normalized Local Citation Score (MNLCS). The Normalized Local Citation Score (NLCS) of a document is calculated by dividing the actual count of local citing items by the expected citation rate for documents with the same year of publication.
a list containing:
map
|
The coupling map as ggplot2 object | |
clusters
|
Centrality and Density values for each cluster. | |
data
|
A list of units following in each cluster | |
nclust
|
The number of clusters | |
NCS
|
The Normalized Citation Score dataframe | |
net
|
A list containing the network output (as provided from the networkPlot function) |
biblioNetwork function to compute a bibliographic network.
cocMatrix to compute a bibliographic bipartite network.
networkPlot to plot a bibliographic network.
## Not run:
data(management, package = "bibliometrixData")
res <- couplingMap(management, analysis = "authors", field = "CR", n = 250, impact.measure="local",
minfreq = 3, size = 0.5, repel = TRUE)
plot(res$map)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.