including the Twitter only group. It is uncommon that pairs connected on Foursquare only mention each other. Mentions are quite common between users who are not connected on any network, which may be as a result of mentioning celebrities and other commercial accounts. This is not the case for hashtags, where we find that almost all of unconnected users share 10 or less hashtags with the exception of outliers. Hashtags distinguish the link type between users better than mentions.

With regards to Foursquare interaction, multiplex ties have the highest probability of multiple colocations, with Foursquare and Twitter only ties having less, and unconnected pairs more so with the exception of some outliers. In terms of distance, Twitter only and unconnected pairs are the furthest apart in terms of most frequented location, making multiplex and Foursquare links more distinguishable through this feature, as those pairs have less distance between their most frequented locations.

Although *there is certainly greater interaction between multiplex links*, followed by Twitter only and Foursquare only links, we would like to eliminate the randomness introduced by the positive results for unconnected pairs (*na*). We propose two multilayer interaction metrics combining heterogenous features from both networks in order to 