Infodemic Detection on Twitter During Pandemic Situation using LDA Topic Modelling

Online social media propagates lot of misinformation during pandemic situation which trigger the human community in to a fear. Hence to avoid the propagation of infodemic during pandemic time. We proposed approach unsupervised infodemic identification using latent dirichlet allocation(LDA). This novel approach initially preprocess the unstructured data from twitter to structured data using NLP preprocessing technique then the data is converted to numerical vector using TF-IDF model. Finally the data is topic modeled for identifying the outlier.