We conducted an exploratory study of 25,000 instant messages from 14 interdisciplinary team networks focused on digital innovation with advanced machine learning technologies. We seek to contribute to theory on network embeddedness in such teams and find that the embeddedness of a message sender influences the messaging activity in teams. However, we further find that the influence of homophily vary depending on the topology of the network, and can contribute to the stratification of these network teams.