---
title: "syphilis traffic"
output: html_document
date: "2024-11-19"
---

```{r}

library(ggplot2)
library(dplyr)

posts_per_year = syphilisall %>%
  filter(!is.na(Year) & Year != 2021) %>%
  group_by(Year) %>%
  summarise(Number_of_Posts = n())

ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts)) +
  geom_line() + 
  geom_point() +  
  labs(title = "Volume of Syphilis Traffic Over Time",
       x = "Year",
       y = "Number of Posts Across All of Reddit")


```



```{r}

sum(is.na(syphilisall$Year))
sum(syphilisall$Year == "")

```



```{r}

posts_per_year = syphilisall %>%
  filter(!is.na(Year) & Year != 2021) %>%  # Exclude NA values and 2021
  group_by(Year, subreddit) %>%            # Group by both 'Year' and 'subreddit'
  summarise(Number_of_Posts = n(), .groups = "drop")  # Count the number of posts per subreddit and year

# Plotting the result
ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
  geom_line(aes(group = subreddit)) +   # Draw a line for each subreddit
  geom_point() +                        # Add points for each year/subreddit combination
  theme(legend.position="none") +
  labs(title = "Volume of Syphilis Traffic Over Time",
       x = "Year",
       y = "Number of Posts per Subreddit")

```

```{r}

unique_values = unique(syphilisall$subreddit)

length(unique_values)

```

```{r}

top_subreddits = syphilisall %>%
  filter(!is.na(Year) & Year != 2021) %>%
  group_by(subreddit) %>%
  summarise(total_posts = n(), .groups = "drop") %>%
  top_n(10, total_posts) 

posts_per_year = syphilisall %>%
  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
  group_by(Year, subreddit) %>%
  summarise(Number_of_Posts = n(), .groups = "drop")

ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
  geom_line(aes(group = subreddit)) + 
  geom_point() +  
  labs(title = "Volume of Syphilis Traffic Over Time",
       x = "Year",
       y = "Number of Posts per Subreddit")

```


```{r}

sum(is.na(syphilisall$subreddit)) 

sum(syphilisall$subreddit == "")


```


```{r}

top_subreddits = syphilisall %>%
  filter(!is.na(Year) & Year != 2021, subreddit != "") %>%
  group_by(subreddit) %>%
  summarise(total_posts = n(), .groups = "drop") %>%
  top_n(10, total_posts) 

posts_per_year = syphilisall %>%
  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
  group_by(Year, subreddit) %>%
  summarise(Number_of_Posts = n(), .groups = "drop")

ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
  geom_line(aes(group = subreddit)) + 
  geom_point() +  
  labs(title = "Volume of Syphilis Traffic Over Time in Top Ten Subreddits",
       x = "Year",
       y = "Number of Posts per Subreddit")

```


```{r}

top_subreddits = syphilistotal %>%
  filter(!is.na(Year) & Year != 2021) %>%
  group_by(subreddit) %>%
  summarise(total_posts = n(), .groups = "drop") %>%
  top_n(10, total_posts) 

posts_per_year = syphilistotal %>%
  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
  group_by(Year, subreddit) %>%
  summarise(Number_of_Posts = n(), .groups = "drop")

ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
  geom_line(aes(group = subreddit)) + 
  geom_point() +  
  labs(title = "Volume of Syphilis Traffic Over Time",
       x = "Year",
       y = "Number of Posts per Subreddit")

```