bibliometrix (version 2.1.1)

thematicMap: Create a thematic map

Description

It creates a thematic map based on co-word network analysis and clustering. The methodology is inspired by the proposal of Cobo et al. (2011).

Usage

thematicMap(M, field = "ID", n = 250, minfreq = 5,
  stemming = FALSE, size = 0.5, repel = TRUE)

Arguments

M

is a bibliographic dataframe.

field

is the textual attribute used to build up the thematic map. It can be field = c("ID","DE", "TI", "AB"). biblioNetwork or cocMatrix.

n

is an integer. It indicates the number of terms to include in the analysis.

minfreq

is a integer. It indicates the minimun frequency of a cluster.

stemming

is logical. If it is TRUE the word (from titles or abtracts) will be stemmed (using the Porter's algorithm).

size

is numerical. It indicates del size of the cluster circles and is a numebr in the range (0.01,1).

repel

is logical. If it is TRUE ggplot uses geom_label_repel instead of geom_label.

Value

a list containing:

map		The thematic map as ggplot2 object
clusters		Centrality and Density values for each cluster.

Details

thematicMap starts from a co-occurrence keyword network to plot in a two-dimesional map the typological themes of a domain.

See Also

biblioNetwork function to compute a bibliographic network.

cocMatrix to compute a bibliographic bipartite network.

networkPlot to plot a bibliographic network.

Examples

# NOT RUN {
data(scientometrics)
res <- thematicMap(scientometrics, field = "ID", n = 250, minfreq = 5, size = 0.5, repel = TRUE)
plot(res$map)

# }