CROSS-LINGUAL SENTIMENT ANALYSIS FOR UKRAINIAN SOCIAL MEDIA SENTIMENT CLASSIFICATION

Understanding the sentiment derived from user-generated content on social media platforms plays a crucial part in today's digital world. However, multilingual datasets create a challenging landscape for sentiment analysis, especially when two or more languages are used interchangeably. This research explores the use of cross-lingual sentiment analysis on Ukrainian social media platforms, where content is expressed in either Ukrainian or russian languages or a mix of them. Using a combination of machine learning and natural language processing techniques, this study established an effective model for cross-lingual sentiment classification.