Event Profiling in Social Media: A Survey with an Application

Abstract

Social media networks are swiftly gaining traction as a platform for discussing what's going on in the real world. The amount of data generated by social media can result in a massive data stream that can be used to get insights into current events and the conversations that surround them. A group of researchers are focusing on profiling event detection algorithms, managing their evolution through time, and deploying them to work in real-time. Event profiling is one of the most important research subjects in natural language processing and understanding, with a wide applications range in various fields and decades of research. This study presents a thorough yet current survey of event extraction from textual data. However, we present a taxonomy of solution approaches as well as a summary of the key definitions for event extraction. We present the event extraction strategies over the big data era. Finally, we show up how to use NLP to outputs events from social media networks and discuss future research directions.