A Machine Learning Approach to Predict Events by Analyzing Bengali Facebook Posts

Facebook is the most popular social media platform all over the world and a huge data repository that can be analyzed to predict events as people express their thoughts on this platform. There are some events that often turn into potential crises and these crises might be avoided if we can predict it earlier. This work aims to predict events that are happening or going to happen by analyzing Bengali Facebook posts and help authorities to take proper security arrangements. In this work, the Naive Bayes Classification model has been used to classify posts as an event. Tokenization, Stopwords removing have been used for data pre-processing. Event phrase matching and 2-Layer Filtering have been used for features collection. Sentiment scores have been measured using Valence Aware Dictionary and Sentiment Reasoner(VADER). Finally, this work predicts four types of events(protesting, celebrating, religious, and neutral) showing 87.5% accuracy.