What's a reasonable distribution to model views over time of... this question? Sorry for the self-referential title ;)

I'd be curious to know what's a curve that could be used to model - in the scale of (say) weeks* - the "engagement lifecycle" of a single news page of an online newspaper in terms of webpage views. The same model could be applied for Stack Exchange questions views too!

What I would intuitively model is the initial spike of visits due to the fact that a new, fresh page is very visible as it's linked in the homepage (triggering also social media reshares) and then the long-term visit behavior e.g. due to that page being reached from links from other webpages, or via search engines.

One possible way would then be the sum of two Poisson processes (the first switching off after some typical characteristic time).

Another possibility would be using something like exponential decay to capture a decay over time of interest (the "freshness" of the content fades, and so does public interest).

Is anyone aware of better alternatives or literature on this?

*I wouldn't model day-night nor weekly seasonality.
One way too look at this problem, by looking at the literature, seems to frame it as an Hawkes process, as e.g. in  Rizoiu et al., https://arxiv.org/abs/1602.06033 .

The paper also cites previous work using other modeling approaches:
One set  of  approaches  describe  popularity  dynamics  [...] as being power-law shapes from either an  exogenous  shock  or  endogenous  relaxation,  a  combination of power-law and exponential decay, multiple
power-law decays with periodicity or a collection of recurrence peaks.