In digital platforms, agents have vast access to information, but the quality of it is unclear. I study this phenomenon as a Bayesian persuasion game with multiple senders that have partial control over the beliefs of a receiver. The receiver knows the signal chosen by all senders but randomly observes the realization of only one such signal. Senders can pool their signals, so the receiver is uncertain about the informativeness of the message received. This uncertainty may incentivize a sender to provide more or less information compared to the benchmark without uncertainty about the sender. The central insight is that each sender’s signal is chosen to affect the average correlation between messages and the state of the world, given the communication strategies of other senders. I derive policy recommendations to improve the quality of the information on platforms like social media.