How to Keep Group Associated when Separating Free Text Fields in R

I'm trying to separate out free text fields until individual words/phrases, while also keeping their association with a group so I can stratify in my graphing later on

here is my original code. I'm trying to add in a "year" variable so I can stratify the different research interests by what year a student is in. I'd like to have a total n for each word, as well as n for each year

example of my data set:

library(tidyverse)
library(tidytext)

data_research_words <- unlist(strsplit(data_research$Please.list.your.research.interests, ", "))

text_df <- tibble(line=1:97, data_research_words)

text_count <- text_df %>% 
  count(data_research_words, sort=TRUE)

Something like this?

library(tidyverse)

# split on commas, to create a separate row for each list element
df <- df |>
  separate_longer_delim("Please.list.your.research.interests", ", ")

# then get the count for each research interest
df |> count(Please.list.your.research.interests)

# ...and the same, but separated also by years
df |> count(Year, Please.list.your.research.interests)

Output:

  Please.list.your.research.interests n
1                    Chronic Diseases 1
2                                 HIV 1
3                                  TB 2
4                            Vaccines 1

      Year Please.list.your.research.interests n
1 1st year                                 HIV 1
2 1st year                                  TB 1
3 1st year                            Vaccines 1
4 2nd year                    Chronic Diseases 1
5 2nd year                                  TB 1