How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. * Email of the corresponding author: yyahn@indiana.edu 1 Diseases, ideas, innovations, and behaviors spread through social networks [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] . With the availability of large-scale, digitized data on social communication [13, 14] , the study of diffusion of memes (units of transmissible information) has become feasible recently [15] [16] [17] [18] . The questions of how memes spread and which will go viral have recently attracted much attention across disciplines, including marketing [6, 19] , network science [20, 21] , communication [22] , and social media analytics [23] [24] [25] . Network structure can greatly affect the spreading process [15, 26, 27] ; for example, infections with small spreading rate persist in scale-free networks [8] . Existing research has attempted to characterize viral memes in terms of message content [22] , temporal variation [16, 24] , influential users [19, 28] , finite user attention [18, 21] , and local
REF studied how the structure of a network affects the diffusion of memes, using data collected from the microblogging Twitter.
Virality Prediction and Community Structure in Social Networks
Scientific Reports 3, 2522 (2013)
Sociology Computer Science Physics Medicine