Detecting and restricting floods of unwanted messages is implemented by cluster analysis over time intervals. Application of streaming machine learning clustering algorithms enables finding clusters of messages (P2P text messages, WHATSAPP, tweets) sharing the same content. Such clusters may be analyzed for finding out offensive messages, unwanted or spam messages, and rumors and take corrective actions as needed. The solution enables visualization of data and/or messages and identification of clusters as the solution works on the data and aggregates data into clusters over time intervals. Corrective actions may be applied on selected clusters based on visualized data clusters or by automated application of defined rules.