Structural Topic Model (Roberts et al. 2016) can be used to extend the former topic modelling approaches by including text metadata on a document level. The meta information can be introduced to the estimation procedure two-fold, via: topical content covariates that shape the word usage within topics

A complete implementation of the STM model and estimation procedure is provided. The main module is contained in src/modules/stm.py; A comprehensive comparison between STM and its direct predecessor CTM is conducted using the implementation provided hereby.

tunity to learn about expert-based modeling efforts. In this paper we reflect on that effort and, based on our collective experience facilitating the development of the LANDFIRE STMs, we offer 10 lessons learned: (1) create a flexible modeling process, (2) incorporate a learn-by-doing method, but know that it takes work, (3) engage a broad spec...

In the following, we’ll work with the stm package Link and Structural Topic Modeling (STM). While a variety of other approaches or topic models exist, e.g., Keyword-Assisted Topic Modeling , Seeded LDA , or Latent Dirichlet Allocation (LDA) as well as Correlated Topics Models (CTM) , I chose to show you Structural Topic Modeling .

Oct 1, 2022 · Structural topic models (STM) take traditional topic models one-step further by incorporating document metadata into the topic estimation. In the present study, document metadata consists of information about the leader such as gender, race, citizenship, organizational level, and job performance.

These models are described in Chapter 12 of the 1st edition. They are explained more briefly in Chapter 22 of the 2nd edition. The Stella models in the book were created years ago and saved as *.stm files. If you use stella Ver 3 - Ver 9, it will recognize the *.stm files on the website.

Sep 8, 2018 · evaluating topic models and understanding model diagnostics, and exploring and interpreting the content of topic models. I’ve been doing all my topic modeling with Structural Topic Models and the stm package lately, and it has been GREAT .

Structural Topic Model (STM), and its implementation in the R package, which provides 1 tools for machine-assisted reading of text corpora.

Variants of this example are available in different places, for STM as well as LDA, SAGE, and a variety of topic models. It’s easy to get confused. There are a variety of prefit STM models for this data that you can download from http://www.princeton.edu/~bms4/VignetteObjects.RData.

Mar 21, 2021 · Training, evaluating, and interpreting topic models | Julia Silge. At the beginning of this year, I wrote a blog post about how to get started with the stm and tidytext packages for topic modeling. I have been doing more topic modeling in various projects, so I wanted to share some workflows I have found useful for