Abstract: Consumer-generated media (CGM) and/or other media are monitored to allow an organization to become aware of, and respond to, issues that may affect how it is perceived by the public. An extract, transform, load (ETL) engine is used to process CGM and other media content, and an analytical engine utilizes a multi-step progressive filtering approach to identify those documents that are most relevant. The filtering approach includes executing broad queries to extract relevant content from different CGM and other sources, extracting text snippets from the relevant content and performing de-duplication, defining organizational identity (e.g., brand name, trade name, or company name) and hot-topic models using a rule-based and statistical-based approach, and using the models together in an orthogonal filtering approach to effectively generate alerts and reports. The methodology is found to be substantially more effective compared to a conventional keyword based approach.