abstracts_seededlda

abstracts_btm

These are topic models trained with different topic model packages.

datasets

Intended to create standard human-in-the-loop validity tests for typical automated content analysis such as topic modeling and dictionary-based methods. This package offers a standard workflow with functions to prepare, administer and evaluate a human-in-the-loop validity test. This package provides functions for validating topic models using word intrusion, topic intrusion (Chang et al. 2009, <https://papers.nips.cc/paper/3700-reading-tea-leaves-how-humans-interpret-topic-models>) and word set intrusion (Ying et al. 2021) <doi:10.1017/pan.2021.33> tests. This package also provides functions for generating gold-standard data which are useful for validating dictionary-based methods. The default settings of all generated tests match those suggested in Chang et al. (2009) and Song et al. (2020) <doi:10.1080/10584609.2020.1723752>.

Chung-hong Chan

oolong

Create Validation Tests for Automated Content Analysis

Marius Sältzer

abstracts_seededlda function

An object of class <code>textmodel_lda</code> (inherits from <code>textmodel</code>, <code>list</code>) of length 10.
An object of class <code>BTM</code> of length 9.

abstracts_seededlda: Topic models trained with the abstracts dataset.

Description

Usage

Arguments

Format