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#' flag_speed_share
#'
#' @description
#' Function to update result based on a narrower time_window.
#'
#' @details
#' This function identifies and marks the subset of results that match a more
#' stringent time window.
#'
#' @param x The original data used to run the \link{detect_groups} function.
#' @param result A data table containing the result data from the \link{detect_groups} function.
#' @param min_participation The minimum participation threshold. Accounts with participation count
#' greater than this threshold will be retained (default parameter equal to
#' the one used in the \link{detect_groups} function).
#' @param time_window The number of seconds within which shared contents are to be considered as
#' coordinated according to the new time_window (default parameter equal to
#' the one used in the \link{detect_groups} function).
#'
#' @return A results data table that includes an additional column set to 1 when the share
#' corresponds with the new time_window, and 0 otherwise.
#'
#' @import data.table
#' @export
flag_speed_share <- function(x, result, min_participation, time_window) {
content_id <- content_id_y <- NULL
if (!inherits(x, "data.table")) {
x <- data.table::as.data.table(x)
}
# update time window
result_update <- result[result$time_delta <= time_window]
# filter by minimum participation
result_update <-
filter_min_participation(x, result_update, min_participation)
# set keys for joining
setkey(result, content_id, content_id_y)
setkey(result_update, content_id, content_id_y)
# create a column name based on the time_window argument
column_name <- paste("time_window", time_window, sep = "_")
# Initialize the new column to 0 for all rows
result[, (column_name) := 0]
# Update the new column to 0 for rows that find a match in result_update
result[result_update, on = .(content_id, content_id_y), (column_name) := 1]
return(result)
}
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