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#' Network data
#'
#' Retrieve data to know which users are connected to which users.
#'
#' @description
#' * `network_data()` returns a data frame that can easily be converted to
#' various network classes.
#' * `network_graph()` returns a igraph object
#'
#' @param x Data frame returned by rtweet function
#' @param e Type of edge/link–i.e., "mention", "retweet", "quote", "reply".
#' This must be a character vector of length one or more. This value will be
#' split on punctuation and space (so you can include multiple types in the
#' same string separated by a comma or space). The values "all" and
#' "semantic" are assumed to mean all edge types, which is equivalent to the
#' default value of `c("mention", "retweet", "reply", "quote")`
#' @return A from/to data edge data frame
#' @seealso network_graph
#' @examples
#' if (auth_has_default()) {
#' ## search for #rstats tweets
#' rstats <- search_tweets("#rstats", n = 200)
#'
#' ## create from-to data frame representing retweet/mention/reply connections
#' rstats_net <- network_data(rstats, c("retweet","mention","reply"))
#'
#' ## view edge data frame
#' rstats_net
#'
#' ## view user_id->screen_name index
#' attr(rstats_net, "idsn")
#'
#' ## if igraph is installed...
#' if (requireNamespace("igraph", quietly = TRUE)) {
#'
#' ## (1) convert directly to graph object representing semantic network
#' rstats_net <- network_graph(rstats)
#'
#' ## (2) plot graph via igraph.plotting
#' plot(rstats_net)
#' }
#' }
#' @export
network_data <- function(x, e = c("mention", "retweet", "reply", "quote")) {
if (isTRUE(e) || (length(e) == 1 && e %in% c("semantics", "all"))) {
e <- c("mention", "retweet", "reply", "quote")
}
stopifnot(is.character(e))
y <- users_data(x)
ids <- character()
screen_names <- character()
if ("mention" %in% e) {
user_mentions <- lapply(x$entities, function(x){
if (has_name_(x, "user_mentions")) {
y <- x$user_mentions
if (length(y$id_str) > 1 || !is.na(y$id_str)) {
return(y[, c("screen_name", "id_str")])
}
}
NULL
})
k <- vapply(user_mentions, is.null, logical(1L))
# If no mention skip
if (!all(k)) {
r <- do.call(rbind, user_mentions[!k])
ids <- c(ids, r$id_str, y[!k, "id_str", drop = TRUE])
screen_names <- c(screen_names, r$screen_name, y[!k, "screen_name", drop = TRUE])
mention <- data.frame(from = rep(y[!k, "id_str", drop = TRUE], times = vapply(user_mentions[!k], nrow, numeric(1L))),
to = r$id_str,
type = "mention")
} else {
mention <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
} else {
mention <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
if ("retweet" %in% e) {
retweet0 <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
# Retweets are those that the text start with RT and a mention but are not quoted
retweets <- startsWith(x$text, "RT @")
if (any(retweets)) {
r <- x[retweets, ]
yr <- y[retweets, ]
user_mentions <- lapply(r$entities, function(x){
y <- x$user_mentions
# Pick the first mention that is the one the tweet is quoting
# Example: 1390785143615467524
return(y[y$indices$start == 3, c("screen_name", "id_str")])
})
um <- do.call(rbind, user_mentions)
ur <- yr[, c("screen_name", "id_str")]
# remove content from deleted users
um_r <- vapply(user_mentions, nrow, numeric(1L))
removed_users <- which(um_r == 0)
for (i in seq_along(ur$id_str)) {
if (i %in% removed_users) {
to_id <- NA_character_
to_screen_name <- NA_character_
} else {
to_id <- um$id_str[i]
to_screen_name <- um$screen_name[i]
}
ids <- c(ids, ur$id_str[i], to_id)
screen_names <- c(screen_names, ur$screen_name[i], to_screen_name)
retweet <- data.frame(from = ur$id_str[i],
to = to_id,
type = "retweet")
retweet0 <- rbind(retweet0, retweet)
}
}
retweet <- retweet0
} else {
retweet <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
if ("reply" %in% e && !all(is.na(x$in_reply_to_user_id_str))) {
reply_keep <- !is.na(x$in_reply_to_user_id_str)
ids <- c(ids, y[["id_str"]][reply_keep], x[["in_reply_to_user_id_str"]][reply_keep])
screen_names <- c(screen_names, y[["screen_name"]][reply_keep], x[["in_reply_to_screen_name"]][reply_keep])
reply <- data.frame(from = y[["id_str"]][reply_keep],
to = x[["in_reply_to_user_id_str"]][reply_keep],
type = "reply")
} else {
reply <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
if ("quote" %in% e && !all(is.na(x$is_quote_status))) {
r <- x[x$is_quote_status, ]
yr <- y[x$is_quote_status, c("screen_name", "id_str")]
# Quotes are from users on entities$user_mentions whose indices start at 3
if (is.data.frame(r$quoted_status$user)) {
um <- r$quoted_status$user[, c("screen_name", "id_str")]
} else {
user_mentions <- lapply(r$quoted_status$user, function(x){
# Pick the first mention that is the one the tweet is quoting
# Example: 1390785143615467524
return(x[, c("screen_name", "id_str")])
})
um <- do.call(rbind, user_mentions)
}
ums <- is.na(um[, 1])
if (!is.null(nrow(ums))) {
um <- um[!ums, ]
yr <- yr[!ums, ]
ids <- c(ids, um$id_str, yr$id_str)
screen_names <- c(screen_names, um$screen_name, yr$screen_name)
quote <- data.frame(from = um$id_str,
to = yr$id_str,
type = "quote")
} else {
quote <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
} else {
quote <- data.frame(from = NA, to = NA, type = NA)[0, , drop = FALSE]
}
out <- rbind(mention, retweet, reply, quote)
out <- out[!is.na(out$type), ]
idsn <- data.frame(id = ids, sn = screen_names)
idsn <- unique(idsn)
stopifnot(all(out$from %in% idsn$id))
stopifnot(all(out$to %in% idsn$id))
attr(out, "idsn") <- as.list(idsn)
out
}
#' @return An igraph object
#' @rdname network_data
#' @export
network_graph <- function(x, e = c("mention", "retweet", "reply", "quote")) {
if (!requireNamespace("igraph", quietly = TRUE)) {
stop(
"Please install the {igraph} package to use this function",
call. = FALSE
)
}
nd <- network_data(x = x, e = e)
idsn <- attr(nd, "idsn")
g <- igraph::make_empty_graph(n = 0, directed = TRUE)
g <- igraph::add_vertices(g, length(idsn$id),
attr = list(id = idsn$id, name = idsn$sn))
edges <- rbind(match(nd[[1]], idsn$id), match(nd[[2]], idsn$id))
igraph::add_edges(g, edges, attr = list(type = nd[[3]]))
}
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