  Discussion about the social network Twitter often concerns its role in
political discourse, involving the question of when an expression of opinion
becomes offensive, immoral, and/or illegal, and how to deal with it. Given the
growing amount of offensive communication on the internet, there is a demand
for new technology that can automatically detect hate speech, to assist content
moderation by humans. This comes with new challenges, such as defining exactly
what is free speech and what is illegal in a specific country, and knowing
exactly what the linguistic characteristics of hate speech are. To shed light
on the German situation, we analyzed over 50,000 right-wing German hate tweets
posted between August 2017 and April 2018, at the time of the 2017 German
federal elections, using both quantitative and qualitative methods. In this
paper, we discuss the results of the analysis and demonstrate how the insights
can be employed for the development of automatic detection systems.
