2020
DOI: 10.3390/e22030265
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Complex Contagion Features without Social Reinforcement in a Model of Social Information Flow

Abstract: Contagion models are a primary lens through which we understand the spread of information over social networks. However, simple contagion models cannot reproduce the complex features observed in real-world data, leading to research on more complicated complex contagion models. A noted feature of complex contagion is social reinforcement that individuals require multiple exposures to information before they begin to spread it themselves. Here we show that the quoter model, a model of the social flow of written … Show more

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Cited by 15 publications
(16 citation statements)
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“…The fundamental difference between this concept is that while simple contagion depends on network connectivity (e.g., epidemiologic contagion of disease), the process of complex contagion of opinion and ideas requires multiple reinforcement that are based on legitimacy in online communities and normative social consensus ( 86 , 87 ). Consequently, the effective propagation of misinformed ideas and anecdotal evidence related with health topics depends on the connectivity between social media users, but in particular on the social legitimacy to share these ideas in different normative contexts ( 88 ). Therefore, the processes of health misinformation spreading that might contribute to the development of infodemics through social media are also related to the social consensus between groups and the social structures among their online communities (i.e., the degree of connectivity between users and the topological configuration of their social network) ( 89 ).…”
Section: Discussionmentioning
confidence: 99%
“…The fundamental difference between this concept is that while simple contagion depends on network connectivity (e.g., epidemiologic contagion of disease), the process of complex contagion of opinion and ideas requires multiple reinforcement that are based on legitimacy in online communities and normative social consensus ( 86 , 87 ). Consequently, the effective propagation of misinformed ideas and anecdotal evidence related with health topics depends on the connectivity between social media users, but in particular on the social legitimacy to share these ideas in different normative contexts ( 88 ). Therefore, the processes of health misinformation spreading that might contribute to the development of infodemics through social media are also related to the social consensus between groups and the social structures among their online communities (i.e., the degree of connectivity between users and the topological configuration of their social network) ( 89 ).…”
Section: Discussionmentioning
confidence: 99%
“…Contagion processes are usually mediated by interactions that should therefore be taken into account into the modeling framework [32][33][34][35]. As a consequence, as for other landmark dynamical processes widely studied within the complex system community, the interplay between the social structure and the contagion dynamics that unfolds upon it has been the focus of many studies [34,36,37]. The mechanisms of a basic contagion dynamics are illustrated in Figure 1.…”
Section: Modeling Social Contagionmentioning
confidence: 99%
“…This way, any system can be encoded as a graph, a mathematical abstraction of the relationships (links) between the constituent units (nodes) of the system. In broad sense, CN science models not only the structure (topology), but also some dynamic phenomena such as information spreading [ 44 ], epidemic processes (both biological [ 45 ], and artificial viruses [ 46 ]) or cascading failures [ 47 , 48 ]. These are very common in large engineered networks: wireless sensor networks [ 49 ], Internet [ 50 ], power grids [ 35 , 51 , 52 ], or transportation networks [ 53 ].…”
Section: Introductionmentioning
confidence: 99%