word_network_plot(text.var, grouping.var = 1:length(text.var), target.words = NULL, stopwords = qdapDictionaries::Top100Words, label.cex = 0.8, label.size = 0.5, edge.curved = TRUE, vertex.shape = "circle", edge.color = "gray70", label.colors = "black", layout = NULL, title.name = NULL, title.padj = -4.5, title.location = 3, title.font = NULL, title.cex = 0.8, log.labels = FALSE, title.color = "black", legend = NULL, legend.cex = 0.8, legend.location = c(-1.54, 1.41), plot = TRUE, char2space = "~~", ...)
label.colors
(+1 length in cloud colors for non-matched terms).TRUE
.TRUE
edges will be curved rather than
straight paths.igraph.vertex.shapes
for more).layout
.NULL
and
NA
are equivalent to 1.0.TRUE
uses a proportional log label for
more readable labels. The formula is: log(SUMS)/max(log(SUMS)))
.
label.size
adds more control over the label sizes.match.string
.NULL
and NA
are equivalent to 1.0."bottomright"
, "bottom"
,
"bottomleft"
, "left"
, "topleft"
, "top"
,
"topright"
, "right"
and "center"
. This places the legend
on the inside of the plot frame at the given location.TRUE
plots a network plot of the words.char.keep
is NULL
, char2space
will activate this
argument.strip
.A network plot of words. Shows the interconnected and supporting use of words between textual units containing key terms.
Words can be kept as one by inserting a double tilde ("~~"
), or
other character strings passed to char2space, as a single word/entry. This is
useful for keeping proper names as a single unit.
## <strong>Not run</strong>: # word_network_plot(text.var=DATA$state) # word_network_plot(text.var=DATA$state, stopwords=NULL) # word_network_plot(text.var=DATA$state, DATA$person) # word_network_plot(text.var=DATA$state, DATA$person, stopwords=NULL) # word_network_plot(text.var=DATA$state, grouping.var=list(DATA$sex, # DATA$adult)) # word_network_plot(text.var=DATA$state, grouping.var=DATA$person, # title.name = "TITLE", log.labels=TRUE) # word_network_plot(text.var=raj.act.1$dialogue, grouping.var=raj.act.1$person, # stopwords = Top200Words) # # #insert double tilde ("~~") to keep dual words (e.g., first last name) # alts <- c(" fun", "I ") # state2 <- mgsub(alts, gsub("\\s", "~~", alts), DATA$state) # word_network_plot(text.var=state2, grouping.var=DATA$person) # # ## Invisibly returns the igraph model # x <- word_network_plot(text.var=DATA$state, DATA$person) # str(x) # library(igraph) # plot(x, vertex.size=0, vertex.color="white", edge.curved = TRUE) # # x2 <- word_network_plot(text.var=DATA$state, grouping.var=DATA$person, # title.name = "TITLE", log.labels = TRUE, label.size = 1.2) # l <- layout.drl(x2, options=list(simmer.attraction=0)) # plot(x2, vertex.size=0, layout = l) # ## <strong>End(Not run)</strong>