A few weeks ago I introduced my students to the notion of dictionaries in python. The obvious way of teaching them, especially in the context of my module, is to use dictionaries to create word frequency lists. In order to make the students understand better why dictionaries are useful, we discussed other ways to produce frequency lists which use only lists. This prompted me to try to think as many ways as possible to produce frequency lists. I also wanted to see how feasible is to use these methods.
The First Shared task on Aggression Identification was organised in conjunction with the First Workshop on Trolling, Aggression and Cyberbullying. The idea of the shared task was fairly simple. Classify a text in one of the following three categories: Overtly Aggressive (OAG), Covertly Aggressive (CAG) and Non-aggressive (NAG). This means that the task is essentially a standard text categorisation task and an approach based on bag-of-words is a good baseline to start with (neither me, nor the task organisers provided a baseline based on bag-of-words, so I don’t know what is the accuracy of the method).