def __get_topic_info(model, count_vectorizer, n_top_words):
    """
    A utility method that generates the detailed topic information
    :param model: LDA model trained int topic_modeller method
    :param count_vectorizer: vectorizer object to get statistical results
    :param n_top_words: num of words for each topic
    :return: topic info
    """
    words = count_vectorizer.get_feature_names()
    topic_info = {}
    for topic_idx, topic in enumerate(model.components_):
        topic_info[topic_idx] = [words[i] for i in topic.argsort()[:-n_top_words - 1:-1]]

    return topic_info