Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection

Understand

The 2020 US Elections have been, more than ever before, characterized by social media campaigns and mutual accusations.

• We investigate in this paper if this manifests also in online communication of the supporters of the candidates Biden and Trump, by uttering hateful and offensive communication.
• We formulate an annotation task, in which we join the tasks of hateful/offensive speech detection and stance detection, and annotate 3000 Tweets from the campaign period, if they express a particular stance towards a candidate.
• Next to the established classes of favorable and against, we add mixed and neutral stances and also annotate if a candidate is mentioned without an opinion expression.