Text Classification Method for Tracking Rare Events on Twitter

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A natural catastrophe is an example of a rare occurrence that does not happen often but may have devastating effects on people and their environment when it occurs. People now have a quick and easy outlet for voicing their ideas thanks to social media. Thus, it may be used by researchers to learn about how individuals react to and think about a wide variety of extremely unusual occurrences. Many research works use social media data to investigate how people's reactions to unusual occurrences in the real world translate to their online personas, thoughts, feelings, and actions. In this piece of work, we offer a method for extracting features and classifying tweets on unusual events like Hurricane Sandy. To begin, a new approach to feature extraction is presented, one that may be used to extract relevant features from each communication. The next step is to offer a Score-based categorization system for differentiating between communications about events and those that are unrelated. Finally, the development of a rare event is analyzed using our suggested approach and the popular keyword search method. The findings show that the suggested method is effective in distinguishing between text messages connected to unusual events and those that are unrelated.