if (!require("tidyverse")) install.packages("tidyverse")
## Loading required package: tidyverse
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
if (!require("ggplot2")) install.packages("ggplot2")
if (!require("tidytext")) install.packages("tidytext")
## Loading required package: tidytext
library(tidyverse)
library(ggplot2)
library(tidytext)
library(stringr) # Part of the tidyverse package
library(forcats) # Part of the tidyverse package
mydata <- read.csv("https://raw.githubusercontent.com/drkblake/Data/main/ConventionSpeeches2020.csv")
tidy_text <- mydata %>%
  unnest_tokens(word,Full.Text) %>%
  count(Author,word, sort = TRUE)
total_words <- tidy_text %>% 
  group_by(Author) %>% 
  summarize(total = sum(n))

# Adding total words column to data file
tidy_text <- left_join(tidy_text,total_words)
## Joining with `by = join_by(Author)`
# Deleting data frames that are no longer needed
rm("total_words")

# TF-IDF
tidy_text_tf_idf <- tidy_text %>%
  bind_tf_idf(word, Author, n) %>%
  arrange(desc(tf_idf))

#Graphing TF-IDF
options(scipen = 999)
tidy_text_tf_idf %>%
  group_by(Author) %>%
  slice_max(tf_idf, n = 12) %>%
  ungroup() %>%
  ggplot(aes(tf_idf, fct_reorder(word, tf_idf), fill = Author)) +
  geom_col(show.legend = FALSE) +
  facet_wrap(~Author, ncol = 2, scales = "free") +
  labs(x = "tf-idf", y = NULL)

The two presedients had very diffferent things to say in thier respective speeches. Most notably, Biden’s most used word was ‘hope’ while Trump’s was ‘Joe Trumps speech uses a low of law and order-esque terms like ’police’, ‘power’, ‘enforcement’ and ‘borders’. The difference in term usage shows a sharp devide between the two men. I DO think it would be interesting to see where the two do align, if at all. Thank you attending my TED talk.