"$\dot \sim$" means "approximately distributed as". It is often used as short hand for something like
$\sqrt n (\bar x - \mu)/\sigma \rightarrow_d N(0,1)$ as $n \rightarrow \infty$
i.e. convergence in distribution, but you are too lazy to write out the necessary $n \rightarrow \infty$ to make the statement actually mathematically rigorous.
(Of course, in the above statement, this is exactly distributed if the $x_i \sim_{iid} N(\mu, \sigma)$. But if $x_i$ are not normal, it would only converge in distribution to $N(0,1)$.)
During grad school, one my professors went on a technical, but justified, rampage about how this notation is often used in an abusive manner. For example, if you were to write
$ \hat p \mathrel{\dot\sim} N(p, \sqrt{p(1-p)/n})$
where $\hat p$ is the standard MLE for a binomial distribution, this seems to imply that $\hat p$ is approximately normal for any n, which is of course not true. We were not allowed to use $\dot \sim$ notation in his class, but rather wrote everything out in the proper "converges in distribution" notation.
None of my other professors cared.