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Jüttner, K., Nowak, P., Imeri, A., & Stock, W. G. (2023). Anonymous COVID-19 channel on Jodel: A quantitative content analysis. In Coman, A., & Vasilache, S. (Eds.), Social Computing and Social Media. HCII 2023 (pp. 324-339). Cham: Springer. (Lecture Notes in Computer Science; 14026).

Abstract.

This paper applied quantitative content analysis to investigate the conversations in theCorona channel of the anonymous social media app Jodel. Twenty thousand four hundred seventy-two postings from the German Corona channelhave been published between March 3, 2020 and February 13, 2021. Those postings were classified into eleven content categories using an automated approach. The results show that, with an overall share of 41%, postings concerning the coronavirus itself and measures to contain the pandemic predominate. An evaluation of the 20 most frequent terms in the dataset underlines this and additionally shows that fellow humans, questions (#question), and temporal aspects are thematized. Interestingly, negative emotions such as fear, panic and worry are shared. At the same time, despite the more serious context of the Corona channel, humor and the search for entertainment seem to matter. The category denial&conspiracy theories comprises the fewest postings. This implies that Jodel, despite its anonymity, does not provide a breeding ground for conspiracy theories and points to a functioning self-regulation of the community.