So, I am wanting to take network data from various time periods of the same network and map it in a way that will allow for clear representation of each time period. For example, taking network data for a 2013-2015 time period, a 2015-217 time period and then a 2020-2021 time period. Importantly, the amount of data will be different and the time periods won't strictly be even (i.e. there might be a 1 year gap between time period a and b and then 5 years between b and c). Also, I think it is important to highlight that these would be 'time-slices' of the same overall network, rather than distinct, unrelated networks.

I am hoping to present these different time-slices in one or two ways. First, I am wanting to be able to place a series of network maps next to each other based on temporal data to show how the network is changing over time. Second, if possible, I would like to produce a video/animation that shows the network changing over time.

I have been doing lots of reading on possible ways to achieve this type of analysis. I have been looking into using stochastics, specifically Markov models or Stochastic Actor-Orientated Modelling (SAOM), both of which I have seen used for similar projects. Only problem is my maths is good, but needs some work before I could comfortably use these approaches, so if stochastics is the way forward, any suggestions for good tutorials?

I have also been looking into Social Sequence Analysis, specifically the use of Network Methods, as outlined by Cornwell (https://www.cambridge.org/core/books/social-sequence-analysis/network-methods-for-sequence-analysis/FFF842AF37364167E23AD03E50650336) which seems promising.

I feel as though I am reading a lot and getting a bit lost in all of the literature. Any advice would be greatly appreciated!