Summarizing twitter posts regarding COVID-19 based on n-grams

The COVID-19 pandemic announced by the World Health Organization has disrupted human lives at different scales, including economy, public health, and people's emotions. Social media databases record huge accumulated information concern this pandemic. Twitter platform is considered one of most active social that enable users to tweet in conversations they are concerned about. problem arises when tweeters want search about a specific topic. They can only sort tweets its recency understand conversation not relevancy. This makes read through what was firstly discussed related Some strategies were developed for summarizing but topics still beginning. current research aims introduce technique present short summary with consuming little time effort. Thus, summarization task started clustering based on latent dirichlet allocation (LDA) method K-means then selected important sentences format summarization. study also compares bigram-based unigram-based Different metrics used evaluate results experiments each stage, output proposal system evaluated using ROUGE metrics.