  Gab is an online social network often associated with the alt-right political
movement and users barred from other networks. It presents an interesting
opportunity for research because near-complete data is available from day one
of the network's creation. In this paper, we investigate the evolution of the
user interaction graph, that is the graph where a link represents a user
interacting with another user at a given time. We view this graph both at
different times and at different timescales. The latter is achieved by using
sliding windows on the graph which gives a novel perspective on social network
data. The Gab network is relatively slowly growing over the period of months
but subject to large bursts of arrivals over hours and days. We identify
plausible events that are of interest to the Gab community associated with the
most obvious such bursts. The network is characterised by interactions between
`strangers' rather than by reinforcing links between `friends'. Gab usage
follows the diurnal cycle of the predominantly US and Europe based users. At
off-peak hours the Gab interaction network fragments into sub-networks with
absolutely no interaction between them. A small group of users are highly
influential across larger timescales, but a substantial number of users gain
influence for short periods of time. Temporal analysis at different timescales
gives new insights above and beyond what could be found on static graphs.
