How to classify language as friendly or aggressive with AI? Just for the purpose of learning I'd like to classify the likeliness of a tweet being in aggressive language or not. 

I was wondering how to approach the problem. I guess I need first train my neural network on a huge dataset of text what aggressive language is. This brings up the question where I would get this data in the first place?

It feels a bit like the chicken and egg problem to me so I wonder how would I approach the problem?
I did a little search and couldn't find any database that has ground truth for aggressiveness. This means that you need to build yourself a database. This might be huge undertaking. Take thousands of messages, and classify them by hand whether they are aggressive or not. This part is quite labor intensive.

Second part is much easier at start but would be pain to optimize (both performance and computational cost). I would suggest you to start with Naive Bayes classifier for this job. That is the preferred classifier for spam detection. ANN would probably not work for this case because the data would be a huge sparse vector. Estimated number of words in English is over a million, which means the input layer of your ANN should be able to scale up to that number. Search for sparse vector classification for additional classifier that can be used in these cases.