USING LIVE DATA STREAMS AND/OR SEARCH QUERIES TO DETERMINE INFORMATION ABOUT DEVELOPING EVENTS

摘要

Techniques and a framework are described herein for gathering information about developing events from multiple live data streams and pushing new pieces of information to interested individuals as those pieces of information are learned. In various implementations, a plurality of live data streams may be monitored. Based on the monitoring, a data structure that models diffusion of information through a population may be generated and applied as input across a machine learning model to generate output. The output may be indicative of a likelihood of occurrence of a developing event and/or a predicted measure of relevancy of the developing event to a particular user. Based on a determination that the likelihood and/or measure of relevancy satisfies a criterion, one or more computing devices may render, as output, information about the developing event.