An Efficient AI Model for Classifier Tweets During Disaster Using Recurrent Neural Networks (RNN)

An Efficient AI Model for Classifier Tweets During Disaster Using Recurrent Neural Networks (RNN)

연구 분야: Artificial Intelligence

학회: International Conference on Intelligent Computing Systems and Applications

During any significant event, particularly during natural catastrophes, social media is an essential information source. It is claimed that data generated by social networking sites would enable regular people to become more situationally aware during disasters and coordinate to help themselves because it is ubiquitous, quick, and accessible. However, as the amount of social media data has grown exponentially, so has the amount of data that are unrelated to a crisis, making it harder for individuals to find the information they need to organise relief efforts, seek assistance, and perhaps even save lives. In this essay, we offer a method for identifying. During times of tragedy, informative messages are posted on social media. Our strategy is to implement this using recurrent neural networks and demonstrate substantial progress.