Table \[tab:datt\] shows the details for each city, in terms of activity and venues, multilayer edges and degrees for each network, where $E^{T \cap F}$ denotes the set of edges, which exist on both Twitter and Foursquare, $E^{T \backslash F}$ and $E^{F \backslash T}$ are the sets of edges on Twitter only and Foursquare only respectively.

Figure \[fig:sf\] additionally illustrates the case of San Francisco, where blue edges represent single-layer links on either Foursquare or Twitter, and pink edges represent multiplex links on both. We use a Fruchterman Reingold graph layout [@Fruchterman1991] to show the core-periphery structure of the network, with larger nodes having a higher global degree $k_{GN}$. In the following section, we discuss the implications of these sets in detail, where we consider all three cities together, and later evaluate each one separately.

Multilayer Analysis
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We begin our analysis by exploring the intersection between the Twitter and Foursquare social networks. We observe user the degree properties across the two networks at a larger scale for all three cities, while later we perform our evaluation on each city separately.

RQ1: Multilayer Degrees
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We introduced two degree metrics based on the multilayer neighbourhood of a node in Equations 