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The storming of the U.S. Capitol on January 6, 2021 has led to the killing of5 people and is widely regarded as an attack on democracy. The storming waslargely coordinated through social media networks such as Parler. Yet little isknown regarding how users interacted on Parler during the storming of theCapitol. In this work, we examine the emotion dynamics on Parler during thestorming with regard to heterogeneity across time and users. For this, wesegment the user base into different groups (e.g., Trump supporters and QAnonsupporters). We use affective computing (Kratzwald et al. 2018) to infer theemotions in the contents, thereby allowing us to provide a comprehensiveassessment of online emotions. Our evaluation is based on a large-scale datasetfrom Parler, comprising of 717,300 posts from 144,003 users. We find that theuser base responded to the storming of the Capitol with an overall negativesentiment. Akin to this, Trump supporters also expressed a negative sentimentand high levels of unbelief. In contrast to that, QAnon supporters did notexpress a more negative sentiment during the storming. We further provide across-platform analysis and compare the emotion dynamics on Parler and Twitter.Our findings point at a comparatively less negative response to the incidentson Parler compared to Twitter accompanied by higher levels of disapproval andoutrage. Our contribution to research is three-fold: (1) We identify onlineemotions that were characteristic of the storming; (2) we assess emotiondynamics across different user groups on Parler; (3) we compare the emotiondynamics on Parler and Twitter. Thereby, our work offers important implicationsfor actively managing online emotions to prevent similar incidents in thefuture.

Online Emotions During the Storming of the U.S. Capitol: Evidence from the Social Media Network Parler