Multilingual sentiment analysis investigating perceptions of globalization

• Main Author: Anagha, Subramaniam Ani
• Other Authors: Erik Cambria
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; Multilingual sentiment analysis; Natural language processing
• Online Access: https://hdl.handle.net/10356/175175
• Institution: Nanyang Technological University

This project seeks to identify trends in perceptions on the topic of globalization by performing sentiment analysis on text data collected from social media posts. A novel methodology of extracting culture-informed sentiments is proposed and tested on a corpus containing text posts from the social media site Reddit in two languages: French and English. To do so, a Graph Convolutional Network is used to train a polarity classification model by extracting commonsense culture-specific knowledge using the SenticNet knowledge base. A variety of sentiment analysis tasks including polarity classification, intensity ranking, toxicity spotting, wellbeing assessment, and personality classification are performed using the Sentic API on two extracted subsets of the corpus and the resulting trends in the data are identified and analyzed.