Visualization of network-based keyword clustering, with frequency and co-occurrence information attached.
keyword_vis(tibble_graph, facet = TRUE, max_nodes = 10, alpha = 0.7)
A tbl_graph
output by keyword_group
.
Whether the figure should use facet or not.
The maximum number of nodes displayed in each group.
The transparency of label. Must lie between 0 and 1. Default uses 0.7.
An object yielded by ggraph
When facet == TRUE
,the function returns a faceted figure with limited number of nodes
(adjuseted by max_nodes
parameter).When facet == FALSE
,all the nodes would be displayed in one
network.Colors are used to specify the groups, the size of nodes is proportional to the keyword frequency,
while the alpha of edges is proportional to the co-occurrence relationship between keywords.
library(akc)
# \donttest{
bibli_data_table %>%
keyword_clean(id = "id",keyword = "keyword") %>%
keyword_group(id = "id",keyword = "keyword") %>%
keyword_vis()
#> Warning: ggrepel: 4 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Warning: ggrepel: 8 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Warning: ggrepel: 11 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Warning: ggrepel: 4 unlabeled data points (too many overlaps). Consider increasing max.overlaps
# without facet
bibli_data_table %>%
keyword_clean(id = "id",keyword = "keyword") %>%
keyword_group(id = "id",keyword = "keyword") %>%
keyword_vis(facet = FALSE)
#> Warning: ggrepel: 3 unlabeled data points (too many overlaps). Consider increasing max.overlaps
# }