Open AccessNeural Embeddings for Text Analysis: A Case Study in Neoliberal Discourse
Author(s) -
Katerina Mandenaki,
Catherine Sotirakou,
Constantinos Mourlas,
Spiros A. Moschonas
Publication year - 2021
Publication title -
journal of education, society and behavioural science
Language(s) - English
Resource type - Journals
ISSN - 2456-981X
DOI - 10.9734/jesbs/2021/v34i1130379
Subject(s) - ideology , neoliberalism (international relations) , sentence , semantics (computer science) , function (biology) , artificial intelligence , pipeline (software) , character (mathematics) , computer science , financialization , discourse analysis , natural language processing , generative grammar , sociology , linguistics , social science , political science , politics , mathematics , philosophy , geometry , evolutionary biology , economics , law , market economy , biology , programming language
This paper examines the notions of neoliberalism and the financialization and marketisation of public life by using computational tools such as sentence embeddings on a novel corpus of neoliberal articles. More specifically, we experimented with distributional semantics along with several Natural Language Processing (NLP) techniques and machine learning algorithms in order to extract conceptual dictionaries and “seed” words. Our findings show that sentence embeddings reveal repetitive patterns constructed around the given concepts and highlight the mechanical character of an ideology in its function of providing solutions, policies and constructing stereotypes. This work introduces a novel pipeline for computer-assisted research in discourse analysis and ideology.