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This paper examines hateful meme-sharing as an everyday behavior among youth, exploring the phenomenon from an explanatory, interactional point of view. This departs from most of the existing field, which tends to focus on political movements and/or meaning making.
Defining hateful memes according the official EU definition of hate-speech, this paper uses a data set consisting of 500 collected memes and interactions. Data is collected though an immersive netnography across both large open and smaller closed social media groups.
To adequately explain behavior in online contexts, data are sampled using a three-dimensional approach: i) known/unknown audience, ii) degree of poster anonymity/identifiability, and iii) closed/open format of the group. The socio-technical features of the various platforms – e.g., modalities of interaction, algorithms, etc. – are included in these three axes.
Based on these data we establish five ideal types of meme posters. First, we find private haters who share hateful content in small groups to strengthen in-group ties. Second, we find public haters who share similar content but in larger groups to gain a perceived sense of status within the specific group only. Third, posting in similar groups we find agitators who aim to provoke a non-likeminded audience. Fourth, propagandeurs post to advocate for an ideological cause, setting them apart from the previous categories, as the previous categories are centered on the reactions to the memes and not the content. Finally, like-hunters cross all of the identified categories, sharing memes with the instrumental purpose of gaining status, such as karma on Reddit.
Thanks to the three-dimensional sampling approach, the study is the first of its kind that empirically shows how sociotechnical features affect hateful behavior. Ultimately, this gives the platforms an increased ability to mitigate the proliferation of hate on their platforms.