Deep learning - aesthetics data modelling
Modeling aesthetics in media is an example of ordinal classification.
One of the most actively maintained datasets for this can be found is Jen Aesthetics
A relatively recent paper using deep learning towards aesthetics modeling is
this

Prior to deep learning era, research groups were trying to translate methods/guidelines used in the photography community to create/capture good quality pictures. There are several guidelines that you can explore with a bit of search online. One popular example is the 'rule of thirds'. Here the primary subject should not be centered in the image but offset and ideally centered at the intersection of 1/3 and 2/3 horizontal and vertical lines. 


This is easy to translate into an algorithm: use salient object recognition or visual attention detection and measure the distance of the center of the salient/attention patch from the 4 rule-of-thirds points. Use this off-set as a feature. The closer the salient patch is to any one of the rule-of-third points, the higher the aesthetic ordinal score for that image.

This is another good paper that explores what makes images popular.

Some researchers have also used the tags or descriptions of photos as features. The objective here is to learn an association between lexical features and image aesthetics. They have sourced their data from online repositories like Digital Photography Challenge.

This subjective task is needless to say very complex. If you plan to address it, I'd recommend beginning with a clear definition of the context within which you aim to address aesthetics. 

Ideally, you'd like to map any given image (media) to some value in [0, ..., 1] $\in \mathcal{R}$.
However, this is very difficult unless you have access to a lot of training data. I suggest trying instead to simplify the problem. If you can reliably map images to just two classes, good aesthetics and bad aesthetics.

You can successively generalize from binary classification to full fledged multi-class ordinal classification, for which you'll very likely have to keep increasing the depth of your CNN.

Good luck! Since, there is more to aesthetics than meets the eye! :-)