I am literally following the steps as presented in chapter 6 of the "Text Mining in R: a Tidy Approach" book. See: https://www.tidytextmining.com/topicmodeling.html
#import libraries
library(topicmodels)
library(tidytext)
#access dataset
data("AssociatedPress")
# set a seed so that the output of the model is predictable
ap_lda <- LDA(AssociatedPress, k = 2, control = list(seed = 1234))
#tidy model object
ap_topics <- tidy(ap_lda, matrix = "beta")
Gives me the following error in the terminal:
Error: No tidy method for objects of class LDA_VEM
What I should be getting, meanwhile is:
## # A tibble: 20,946 x 3
## topic term beta
## <int> <chr> <dbl>
## 1 1 aaron 1.69e-12
## 2 2 aaron 3.90e- 5
## 3 1 abandon 2.65e- 5
## 4 2 abandon 3.99e- 5
## 5 1 abandoned 1.39e- 4
## 6 2 abandoned 5.88e- 5
## 7 1 abandoning 2.45e-33
## 8 2 abandoning 2.34e- 5
## 9 1 abbott 2.13e- 6
## 10 2 abbott 2.97e- 5
## # ... with 20,936 more rows
Why am I seeing this error instead of the desired result?
You are not the first person to run into this problem, but it is very difficult to reproduce. In fact, I personally have never been able to reproduce the error. However, I know it is a real problem because, well... If you'd like to see other people also struggling, check out here or here or here or here.
As best as I can tell, this is likely a bug in the topicmodels package, related to S4 registration. You can avoid running into this by not saving .RData between sessions and always starting from a fresh R session when you open up work.