Sentiment analysis on Swahili - English code switched tweets via transfer learning

Abstract

Sentiment analysis is a technique that is used to determine the sentiment, or emotional content, of a piece of text. When applied to code switched data, sentiment analysis can be used to determine the sentiment of text that contains words from multiple languages. This is a challenging task, as code switching can introduce complexity and ambiguity into the text. This study will present the use of transfer learning for sentiment analysis on Swahili-English codeswitched data using deep neural network models. This study will focus on the use of transfer learning in conducting sentiment analysis on Swahili-English code switched data. The study will consider two pre-trained deep learning algorithms, that is mBERT and SwahBERT. This study will use these pre-trained deep learning models to conduct sentiment analysis on Swahili-English code switched tweets gathered between the period 29th March 2022 to 15th August 2022 and compare their performance using accuracy, specificity, precision, recall and f1 score metrics.