While intolerant, abusive and hateful speech online has received a lot of attention by researchers in social, media and communication studies, its linguistic aspects have yet to be thoroughly investigated. This book contributes to filling this gap by showcasing how a linguistic perspective has much to offer in unravelling exactly what is occurring. With a common goal to interrogate the linguistic aspects of negative online behaviours on different social media platforms and against different targets, the authors approached the phenomenon from a different methodological frameworks. While primarily interested in identifying, describing and understanding intolerant, abusive and hateful speech online thoroughly and comprehensively, they also had a common belief that their work could inform efforts to contain or mitigate the impact of negative online behaviours regardless of where they occur.
The paper examines the comments sections of the most visited Facebook news pages in Slovenia between 2010 and 2017. The research focuses on socially unacceptable discourse (SUD) concerning two topics then dividing the public; namely, the refugee crisis and the rights of LGBT people. The results show that the share of comments with SUD is high and stable, representing approximately half of all the comments on both topics and all three news pages. Surprisingly, there are few differences among the news outlets as regards the internal structure and characteristics of SUD, although significant differences were found in the extent of SUD among the portals. On the other hand, the results did not confirm the presence of organised hate cam-paigns or the connectedness of commentators. The results offer one of the first insights into the characteristics of the commenting culture in Slovenia, the timeframe of commenting and the connectedness of commentators.
The paper examines the part-of-speech tagging accuracy and necessary annotation effort differences between a) normalising the texts and then tagging it with a tool developed for standard languages and b) domain adaptation, i.e. manually annotating a sample of the non-standard language and tagging it directly