couplingMap {bibliometrix} | R Documentation |

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,
community.repulsion = 0.1,
stemming = FALSE,
size = 0.5,
n.labels = 1,
repel = TRUE,
cluster = "walktrap"
)
```

`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). |

`community.repulsion` |
is a real. It indicates the repulsion force among network communities. It is a real number between 0 and 1. Default is |

`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. |

`cluster` |
is a character. It indicates the type of cluster to perform among ("optimal", "louvain","leiden", "infomap","edge_betweenness","walktrap", "spinglass", "leading_eigen", "fast_greedy"). |

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)
```

[Package *bibliometrix* version 4.1.4 Index]