The meaning of sentiment analysis of UN speeches on the Russia-Ukraine war: a comparative study using VADER and BERT NLP techniques

Abstract

The use of natural language processing (NLP) to analyze political speeches provides valuable insights into global politics. Political discourse shapes public opinion and international relations, particularly in forums like the United Nations (UN). Sentiment analysis, a key NLP technique, helps uncover the emotional and strategic aspects of such speeches. This study evaluates the sentiment in UN speeches on the Russia-Ukraine conflict using two advanced tools, VADER and BERT. A mixed-method approach compares their effectiveness and incorporates narrative analysis to explore context and implications. Results highlight a sentiment favoring global cooperation and Ukraine, challenging claims of a North–South divide, and demonstrate the benefits of a two-stage research approach.