Epistemological aspect of topic modelling in the social sciences: Latent Dirichlet Allocation
Year: 2022
Type: article
Abstract: Aware of the challenges faced by the social sciences in publishing a massive volume of research papers, it is worth looking at a novel but no longer so new ways of machine learning for the purposes of literature review. To this end, I explore a probabilistic topic model called Latent Dirichlet Allocation (LDA) in the context of the epistemological challenge of analysing texts on social welfare. This paper aims to describe how the LDA algorithm works for large corpora of data, along with its advantages and disadvantages. This preliminary characterisation of an inductive method for automated text analysis is intended to give a brief overview of how LDA can be used in the social sciences.
Source: Przegląd Krytyczny
Author: Mariusz Baranowski
Institution: Adam Mickiewicz University in Poznań
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4292575185