Topic modelling using LDA

Question

While defining corpus and dictionary for building the LDA model by defining topics how can we different topics keywords

It is working while giving an explicitly topic number, but I want that to be iterated.

Preparing dictionary and corpus

from gensim import corpora

dictionary = corpora.Dictionary(doc_clean)

corpus = [dictionary.doc2bow(doc) for doc in doc_clean]

Building LDA Model

lda_model = gensim.models.ldamodel.LdaModel(corpus = corpus , id2word=dictionary , num_topics=10 , random_state=100, update_every=1 , chunksize=100 , passes=10 , alpha='auto' , per_word_topics=True)

Printing the Keywords in topics

topics = print(lda_model.print_topic(6))

doc_lda = lda_model[corpus]

I want to know how can we iterate the topics instead of giving manually each time topic number

Answer 1

If I understood your ask correctly, all you need is:

topics = []
num_topics=10
for i in range((num_topics)):
    topics.append(lda_model.print_topic(i+1))