Sentiment Analysis during Jakarta Flood for Emergency Responses and Situational Awareness in Disaster Management using BERT

Social media provide valuable information for disaster risk reduction as well as a disaster emergency response. Previous studies claim that social media data can be used in the emergency response effort, which is worthwhile for the Government, BNPB, as well as the community, to get a direct and credible information about the ongoing disaster situations. However, the social media data has not been widely used for emergency response and situational awareness in Indonesia. Therefore, in this paper we implement BERT method applied to a set of tweets related to Jakarta Flood in early 2020. We have crawled the tweet dataset during the Jakarta flood disaster in early 2020 which had become a trending topic on Twitter. We aim to identify the relevance tweets that may provide useful information related to emergency responses in disaster management. The experimental results indicate promising outcomes. However, the quality of the dataset greatly influences the system performance.