What does 'seed' do in in 'ldatuning' to determine LDA topic frequency (in R)?

Question

I have been trying out different ways of determining topic frequency in LDA (in R) and have stumbled across the very useful-looking package ldatuning but cannot really figure out the control parameter and particularly the example value for seed.

Here is the example code from the website:

library("topicmodels")
data("AssociatedPress", package="topicmodels")
dtm <- AssociatedPress[1:10, ]

result <- FindTopicsNumber(
  dtm,
  topics = seq(from = 2, to = 15, by = 1),
  metrics = c("Griffiths2004", "CaoJuan2009", "Arun2010", "Deveaud2014"),
  method = "Gibbs",
  control = list(seed = 77),
  mc.cores = 2L,
  verbose = TRUE
)

I played around with the parameters a little bit and noticed that changes in the value for seed change the output graphs quite significantly. Can someone please explain what the 77 in this case stands for and how the value for seed should be selected?

Also, I couldn't find any other options for what to enter for control and what effect that has on the result. If anyone can provide some guidance here that would be great.

Answer 1

seed : Object of class "integer"; used to set the seed in the external code for VEM estimation and to call set.seed for Gibbs sampling. For Gibbs sampling it can also be set to NA (default) to avoid changing the seed of the random number generator in the model fitting call.