부산대학교 도서관

The most popular method for analysing a text is sentiment analysis. It is quite helpful for social media monitoring since it enables us to get a broad sense of what the general population thinks about particular issues. However, it is also handy for business analysis and various other situations in which the text needs to be analyzed. In this paper we present a solution up to 90% correctly classify whether a tweet is associated with a disaster. Using a multi-detector ensembled approach, we create a reliable model that can predict accurately in situations powered by multiple CNNs and BERT detectors.