The objectives are to: 1. Enhance previous work to detect emerging practices, recommendation, and collaborative filtering. 2. Develop programming interfaces and implementations for data cleansing, message annotation, classification and clustering, topic evolution, and recommendation. 3. Develop content management and learning for multimedia “Big Data” based on holistic “Divide & Conquer” philosophy. 4. Perform a distributed computing and storage platform for content management and preservation. 5. Research and develop, ever-evolving and self-adapting clouds of evolutionary feature synthesizers and classifier networks to “learn” and “mimic” the human audio-visual system based categorization for the audio-visual content. 6. Study user roles, content, and temporal thread evolution in multimodal environments (e.g. thread-based commenting). 7. Develop a representation framework (language, inference algorithms) and computational models that accurately capture the nuances of online behavior, enabling automated reasoning, e.g. prediction of thread evolution, intervention planning.