Nothing
#' Piracy and PIPA/SOPA
#'
#' This dataset contains observations on all 100 US Senators and 434 of the
#' 325 US Congressional Representatives related to their support of anti-piracy
#' legislation that was introduced at the end of 2011.
#'
#' The Stop Online Piracy Act (SOPA) and the Protect Intellectual Property Act
#' (PIPA) were two bills introduced in the US House of Representatives and the
#' US Senate, respectively, to curtail copyright infringement. The bill was
#' controversial because there were concerns the bill limited free speech
#' rights. ProPublica, the independent and non-profit news organization,
#' compiled this dataset to compare the stance of legislators towards the
#' bills with the amount of campaign funds that they received from groups
#' considered to be supportive of or in opposition to the legislation.
#'
#' For more background on the legislation and the formulation of
#' \code{money_pro} and \code{money_con}, read the documentation on ProPublica,
#' linked below.
#'
#' @name piracy
#' @docType data
#' @format A data frame with 534 observations on the following 8 variables.
#' \describe{
#' \item{name}{Name of legislator.}
#' \item{party}{Party affiliation as democrat (\code{D}), Republican (\code{R}), or Independent (\code{I}).}
#' \item{state}{Two letter state abbreviation.}
#' \item{money_pro}{Amount of money in dollars contributed to the legislator's campaign in 2010 by groups generally thought to be supportive of PIPA/SOPA: movie and TV studios, record labels.}
#' \item{money_con}{Amount of money in dollars contributed to the legislator's campaign in 2010 by groups generally thought to be opposed to PIPA/SOPA: computer and internet companies.}
#' \item{years}{Number of years of service in Congress.}
#' \item{stance}{Degree of support for PIPA/SOPA with levels \code{Leaning No}, \code{No}, \code{Undecided}, \code{Unknown}, \code{Yes}}
#' \item{chamber}{Whether the legislator is a member of either the \code{house} or \code{senate}.}
#' }
#' @source \url{https://projects.propublica.org/sopa}
#' The list may be slightly out of date since many politician's perspectives on
#' the legislation were in flux at the time of data collection.
#' @keywords Congress SOPA PIPA copyright infringement legislation datasets
#' @examples
#'
#' library(dplyr)
#' library(ggplot2)
#'
#' pipa <- filter(piracy, chamber == "senate")
#'
#' pipa |>
#' group_by(stance) |>
#' summarise(money_pro_mean = mean(money_pro, na.rm = TRUE)) |>
#' ggplot(aes(x = stance, y = money_pro_mean)) +
#' geom_col() +
#' labs(
#' x = "Stance", y = "Average contribution, in $",
#' title = "Average contribution to the legislator's campaign in 2010",
#' subtitle = "by groups supportive of PIPA/SOPA (movie and TV studios, record labels)"
#' )
#'
#' ggplot(pipa, aes(x = stance, y = money_pro)) +
#' geom_boxplot() +
#' labs(
#' x = "Stance", y = "Contribution, in $",
#' title = "Contribution by groups supportive of PIPA/SOPA",
#' subtitle = "Movie and TV studios, record labels"
#' )
#'
#' ggplot(pipa, aes(x = stance, y = money_con)) +
#' geom_boxplot() +
#' labs(
#' x = "Stance", y = "Contribution, in $",
#' title = "Contribution by groups opposed to PIPA/SOPA",
#' subtitle = "Computer and internet companies"
#' )
#'
#' pipa |>
#' filter(
#' money_pro > 0,
#' money_con > 0
#' ) |>
#' mutate(for_pipa = ifelse(stance == "yes", "yes", "no")) |>
#' ggplot(aes(x = money_pro, y = money_con, color = for_pipa)) +
#' geom_point() +
#' scale_color_manual(values = c("gray", "red")) +
#' scale_y_log10() +
#' scale_x_log10() +
#' labs(
#' x = "Contribution by pro-PIPA groups",
#' y = "Contribution by anti-PIPA groups",
#' color = "For PIPA"
#' )
"piracy"
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.