Sentiment Analysis of Air Pollution in Jakarta Using the Bidirectional Encoder Representations from Transformers (BERT) Method
Year: 2025
Type: conference-paper
Abstract: Air pollution represents a critical environmental challenge in Jakarta, significantly affecting public health and overall quality of life. This study aims to examine public sentiment regarding air pollution in Jakarta through the application of the Bidirectional Encoder Representations from Transformers (BERT) methodology. The selection of this method is based on its proficiency in comprehending contextual nuances within textual data, thereby facilitating a more precise sentiment analysis. The data utilized in this research is sourced from social media platforms, particularly Twitter, which serves as a vibrant and informative repository of public opinion. The findings of the analysis indicate a predominance of negative sentiments concerning air pollution, influenced by various factors such as governmental policies and prevailing environmental conditions. This research aspires to enhance understanding of public perceptions related to air pollution and contribute to more informed decision-making in environmental policy formulation.
Authors: Shiva Aulia Anjani, Mya Septiani, Fawwaz Alfauzi, Sudin Saepudin, Muhamad Muslih, Carti Irawan
Institution: Nusa Putra University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4415403805