topics_summary: Mean topic likelihoods summary

In sdaume/topicsplorrr: A Package Supporting Topical Text Analysis, Exploration and Visualization

Description

topics_summary summarizes the mean likelihood of topics across all documents combined with a set of suitable labels. This is a convenience function to create summary visualizations or interactive tables.

Usage

topics_summary(topicsByDocDate, topicLabels)

Arguments

topicsByDocDate	a dataframe as returned by topics_by_doc_date
topicLabels	a dataframe as returned by topics_terms_map, associating a topic_id with a suitable topic_label.

Value

@return a dataframe with term frequencies by chosen timebin, where:

topic_id

the unique topic identifier assigned by a topic model

topic_label

a character vector of representative labels for topic_id

mean_gamma

the mean likelihood of topic_id across all documents

sdaume/topicsplorrr documentation built on Dec. 22, 2021, 11:11 p.m.