Abstract
In this paper, we discuss how emotional messages sent during crisis events shape the communication patterns on Twitter. To this end, we analyzed a data-set consisting of 23.3 million tweets that have been sent during eighteen different crisis events in ten different countries. In particular, we use the novel concept of emotion-exchange motifs to uncover the elementary building blocks of complex emotion-exchange networks. Our results show that not all negative emotions are exchanged in the same way, nor do they result in the same communication structures. For example, we found that there is a specific set of emotions which are sent in response to messages including sadness and disgust (e.g., sadness attracts joy/love, while disgust attracts anger). The exchange of fear, on the other hand, is highly representative for its reciprocity and is highly associated with an information seeking behavior. We also found that the expression of positivity is characteristic for the emergence of a cyclic triad communication pattern. In contrast, the exchange of negative emotions is characteristic for a triadic communication structure that not only shows a broadcasting behavior but also reciprocity. Compared to single-emotion exchanges within a triadic pattern, the exchange of a mixture of emotions leads to more complex communication structures.
Highlights
Emotional content shared via online social networks (OSNs) has the potential to influence public response and, subsequently, human ac tions
We examined the role of emotion-exchange motifs during man-made crisis events (Kusen & Strembeck, 2019, Kusen & Strembeck, 2020) and natural disasters (Kusen & Strembeck, 2020) and showed that while some motifs are characteristic for a Twitter-like communication in general, others are characteristic for the communication of positive or negative emotions
In our data-set, we found that the average emotional intensities of fear and sadness dominate over the remaining emotions during natural disasters, anger and fear during riots, and fear and anger during shootings and terror attacks
Summary
Emotional content shared via online social networks (OSNs) has the potential to influence public response and, subsequently, human ac tions. Wang et al (2016) and Starbird, Maddock, Achterman and Mason (2014) showed that messages conveying intense negative emotions (such as panic or anger) may lead to negative aftereffects for individuals or groups of people One such example was observed during the 2013 Boston marathon bombing when a man was falsely identified as the bomber on Twitter (Starbird, Maddock, Orand, Achterman, & Mason, 2014). Norris, Galea, Friedman and Watson (2006) indi cated that crisis events are most often experienced collectively In this context, the information available on OSNs influences people’s attitude and behavior (Bakker, van Bommel, Kerstholt, & Giebels, 2018), and, according to Sutton and Shklovski (2008), triggers the human need for information dissemination and conversation
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