Random LDA Topic Model Generation with Gensim

This function generates a random LDA topic model using the gensim library. It accepts a list of documents, the number of topics, and the number of passes as parameters.

Technology Stack : gensim, numpy, random

Code Type : Python Function

Code Difficulty : Intermediate

                
                    
import gensim
import numpy as np
import random

def generate_random_topic_model(document_list, num_topics, passes):
    """
    Generates a random LDA topic model using gensim library.
    """
    # Create a dictionary representation of the documents.
    dictionary = gensim.corpora.Dictionary(document_list)
    
    # Convert dictionary to a Bag of Words (BoW) corpus.
    corpus = [dictionary.doc2bow(doc) for doc in document_list]
    
    # Generate random LDA model.
    random.seed(42)  # For reproducibility
    lda_model = gensim.models.ldamodel.LdaModel(
        corpus=corpus,
        id2word=dictionary,
        num_topics=num_topics,
        random_state=42,
        passes=passes,
        alpha='auto',
        per_word_topics=True
    )
    
    # Print the LDA model.
    print(lda_model.print_topics())

# Example usage:
# document_list = [['python', 'data', 'science'], ['gensim', 'lda', 'topic'], ['model', 'corpus', 'dictionary']]
# generate_random_topic_model(document_list, num_topics=2, passes=10)