Flexiable visualization of network (alternative to 'keyword_vis')

Providing flexible visualization of keyword_vis. The group size would be showed, and user could extract specific group to visualize.

keyword_network(
  tibble_graph,
  group_no = NULL,
  facet = TRUE,
  max_nodes = 10,
  alpha = 0.7
)

Arguments

tibble_graph

A tbl_graph output by keyword_group.

group_no

If one wants to visualize a specific group, gives the group number. Default uses NULL,which returns all the groups.

facet

Whether the figure should use facet or not.

max_nodes

The maximum number of nodes displayed in each group.

alpha

The transparency of label. Must lie between 0 and 1. Default uses 0.7.

Value

An object yielded by ggraph

Details

If the group_no is not specified, when facet == TRUE, the function returns a faceted figure with limited number of nodes (adjuseted by max_nodes parameter). The "N=" shows the total size of the group.

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.

If the group_no is specified, returns the network visualization of the group. If you want to display all the nodes, set max_nodes to Inf.

See also

ggraph,keyword_vis

Examples

 library(akc)
# \donttest{
 bibli_data_table %>%
   keyword_clean(id = "id",keyword = "keyword") %>%
   keyword_group(id = "id",keyword = "keyword") %>%
   keyword_network()
#> Joining, by = c("name", "freq", "group")
#> 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


# use color with `scale_fill_`
 bibli_data_table %>%
   keyword_clean(id = "id",keyword = "keyword") %>%
   keyword_group(id = "id",keyword = "keyword") %>%
   keyword_network() + ggplot2::scale_fill_viridis_d()
#> Joining, by = c("name", "freq", "group")
#> 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_network(facet = FALSE)
#> Joining, by = c("name", "freq", "group")
#> Warning: ggrepel: 3 unlabeled data points (too many overlaps). Consider increasing max.overlaps


# get Group 5
 bibli_data_table %>%
   keyword_clean(id = "id",keyword = "keyword") %>%
   keyword_group(id = "id",keyword = "keyword") %>%
   keyword_network(group_no = 5)

# }