Evolution of Topics in the Psychology Domain
Date
2020
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Tartu Ülikool
Abstract
Topic modeling is a set of statistical methods for modeling collections of
discrete data such as text corpora. It is used as a text-mining tool to discover the hidden
semantic structures in a text body. Latent Dirichlet Allocation, a particular method for
topic modeling is a generative probabilistic model that models texts as a mixture of
underlying topics. In this thesis, Latent Dirichlet Allocation is used on a large corpus
of texts from the domain of psychology. A model with 100 topics is generated, and the
resulting topics are labeled. The occurrence of the topics is analysed over a time span
of 40 years. The
Description
Keywords
Topic models, psychology, Latent Dirichlet Allocation, semantic models