ipo: Facebook, Google, and LinkedIn IPO filings

In OpenIntroStat/openintro-r-package: Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

Facebook, Google, and LinkedIn IPO filings

Description

On Feb 1st, 2011, Facebook Inc. filed an S-1 form with the Securities and Exchange Commission as part of their initial public offering (IPO). This dataset includes the text of that document as well as text from the IPOs of two competing companies: Google and LinkedIn.

Usage

ipo

Format

The format is a list of three character vectors. Each vector contains the line-by-line text of the IPO Prospectus of Facebook, Google, and LinkedIn, respectively.

Details

Each of the three prospectuses is encoded in UTF-8 format and contains some non-word characters related to the layout of the original documents. For analysis on the words, it is recommended that the data be processed with packages such as tidytext. See examples below.

Source

All IPO prospectuses are available from the U.S. Securities and Exchange Commission: Facebook, Google, LinkedIn.

References

Zweig, J., 2020. Mark Zuckerberg: CEO For Life?. WSJ.

Examples

library(tidytext)
library(tibble)
library(dplyr)
library(ggplot2)
library(forcats)

# Analyzing Facebook IPO text

facebook <- tibble(text = ipo$facebook, company = "Facebook")

facebook %>%
  unnest_tokens(word, text) %>%
  anti_join(stop_words) %>%
  count(word, sort = TRUE) %>%
  slice_head(n = 20) %>%
  ggplot(aes(y = fct_reorder(word, n), x = n, fill = n)) +
  geom_col() +
  labs(
    title = "Top 20 most common words in Facebook IPO",
    x = "Frequency",
    y = "Word"
  )

# Comparisons to Google and LinkedIn IPO texts

google <- tibble(text = ipo$google, company = "Google")
linkedin <- tibble(text = ipo$linkedin, company = "LinkedIn")

ipo_texts <- bind_rows(facebook, google, linkedin)

ipo_texts %>%
  unnest_tokens(word, text) %>%
  count(company, word, sort = TRUE) %>%
  bind_tf_idf(word, company, n) %>%
  arrange(desc(tf_idf)) %>%
  group_by(company) %>%
  slice_max(tf_idf, n = 15) %>%
  ungroup() %>%
  ggplot(aes(tf_idf, fct_reorder(word, tf_idf), fill = company)) +
  geom_col(show.legend = FALSE) +
  facet_wrap(~company, ncol = 3, scales = "free") +
  labs(x = "tf-idf", y = NULL)

OpenIntroStat/openintro-r-package documentation built on Nov. 19, 2023, 4:58 p.m.