Burst detection is a research area that focuses on identifying sudden and temporary increases in activity or output within a given system or dataset. This could include bursts of social media activity, bursts of network traffic, or bursts of sales in a retail environment. The goal of burst detection is to detect and analyze these bursts in order to gain insights into the underlying patterns, trends, or anomalies in the data. Researchers in this area often use statistical methods, machine learning techniques, and data mining algorithms to detect bursts and interpret their significance. Burst detection is commonly used in fields such as social media analysis, network traffic analysis, and anomaly detection.