diff --git a/scripts/Xpbtid.R b/scripts/Xpbtid.R
new file mode 100644
index 0000000..89dbe6e
--- /dev/null
+++ b/scripts/Xpbtid.R
@@ -0,0 +1,169 @@
+# Load Libraries
+library("rvest")
+library("tidyverse")
+library("ggplot2")
+library("wordcloud")
+library("tidytext")
+library("tinytex")
+library("syuzhet")
+library("lubridate")
+library("scales")
+library("reshape2")
+library("dplyr")
+
+# This scraping is getting all of the internal links
+
+#Page 1 Scrape
+pol_threads1 <- read_html("https://boards.4channel.org/pol/") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 2 Scrape
+pol_threads2 <- read_html("https://boards.4channel.org/pol/2") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 3 Scrape
+pol_threads3 <- read_html("https://boards.4channel.org/pol/3") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 4 Scrape
+pol_threads4 <- read_html("https://boards.4channel.org/pol/4") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+
+#Page 5 Scrape
+pol_threads5 <- read_html("https://boards.4channel.org/pol/5") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 6 Scrape
+pol_threads6 <- read_html("https://boards.4channel.org/pol/6") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 7 Scrape
+pol_threads7 <- read_html("https://boards.4channel.org/pol/7") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 8 Scrape
+pol_threads8 <- read_html("https://boards.4channel.org/pol/8") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 9 Scrape
+pol_threads9 <- read_html("https://boards.4channel.org/pol/9") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+#Page 10 Scrape
+pol_threads10 <- read_html("https://boards.4channel.org/pol/10") %>%
+  html_elements("a") %>%
+  html_attr('href')
+
+# Combining all of the threads into 1 Vector
+df_pol <-      c(pol_threads1, 
+                 pol_threads2, 
+                 pol_threads3, 
+                 pol_threads4, 
+                 pol_threads5, 
+                 pol_threads6, 
+                 pol_threads7, 
+                 pol_threads8, 
+                 pol_threads9,
+                 pol_threads10)
+
+#tibble makes a table out of data from the scraped links
+pol_table <- tibble(txt = df_pol)
+
+# Choosing all of the links that look like: "4chan.org/pol/thread/this-is-a-thread/"
+df_links <- pol_table %>% 
+  filter(str_detect(txt, "(thread/[0-9]{6,}[/][a-z]{1,})"))
+
+# Next step is appending on "https://boards.4chan.org/pol/" before the "thread/this-is-a-thread".
+df_links$txt <- paste("https://boards.4chan.org/pol/", df_links$txt, sep = "")
+
+# This code will "apply" the 
+# "read_html" 
+# "html_elements" and 
+# "html_attr"
+# to each row in the data frame
+threads <- lapply(df_links$txt, function(x) {
+  read_html(x) %>%
+    html_elements("span") %>%
+    html_attr("class")})
+
+# This gets all class elements from HTML and puts them under 1 column
+threads_rbind <- do.call(rbind.data.frame, threads)
+threads_col <- tibble(txt = threads_rbind)
+threads_col_all <-data.frame(txt = c(t(threads_col)), stringsAsFactors=FALSE)
+
+# Break up all of the sentences into single words
+# Also filters everything except: example -> "id_A1b2c45d"
+tidy_pol_IDs <- threads_col_all %>% 
+  unnest_tokens(word, txt, format = "text") %>% 
+  filter(str_detect(word, "(id_[a-zA-z0-9]{8})"))
+
+
+# === Import CSV as tidy_pol_IDs ===
+# tidy_pol_IDs <- read.csv("~/Documents/Stats/4ChanScraper/Aug 28 2023 06:01:27 PM.csv")
+
+# Shows the top 10 IDs, and displays number
+# of their posts for all threads.
+tidy_pol_sorted_IDs <- tidy_pol_IDs %>% 
+  count(word, sort = TRUE)
+
+# Useless code, but shows the bottom 10 IDs
+# A few hundred posters only post twice.
+tidy_pol_bottom_10_IDs <- tidy_pol_IDs %>% 
+  count(word, sort = TRUE) %>% 
+  tail(50)
+
+# Counts all occurances of the unique ID showing up in threads
+count_by_IDs <- tidy_pol_IDs %>% 
+  count(word, sort = TRUE) %>% 
+  tail(50)
+
+# Combines all counts of each poster's post
+# e.g., Unique IDs posted twice, 
+# for a total of 500 times across all threads
+# i.e. 2bptid
+count_by_n <- tidy_pol_sorted_IDs %>% 
+  count(n, sort = TRUE)
+
+
+# =========== Time to Visualize ===========
+
+# Plots the biggest contributers for posts
+# in all threads
+tidy_pol_sorted_IDs %>% 
+  top_n(30) %>% 
+  mutate(word = reorder(word, n)) %>% 
+  ggplot(aes(word, n)) +
+  geom_col(fill="darkblue") + 
+  xlab("Words") +
+  ylab("Count") +
+  coord_flip() +
+  theme_dark()
+
+# Plots total observation for X posts by this ID
+# Example: 
+# plots X number of observations for 2 posts by this ID
+# Then it orders the top 20 frequencies starting from zero.
+count_by_n %>% 
+  top_n(20) %>% 
+  mutate(reorder(n, nn)) %>% 
+  ggplot(aes(n, nn)) +
+  geom_col(fill = "darkblue") + 
+  xlab("Number of Posts per ID") +
+  ylab("Observed Counts of X posts") +
+  coord_flip() +
+  theme_dark()
+
+# Time to Save the Data
+timestamp <- format(Sys.time(), "%b %d %Y %X")
+filename <- paste0("~/Documents/Stats/4ChanScraper/Pol-IDs-",timestamp,".csv")
+write.csv(tidy_pol_IDs, file = filename)