This paper aims to provide new insights on the concept of virality and on its structure - especially in social networks. We argue that: (a) virality is a phenomenon strictly connected to the nature of the content being spread (b) virality is a phenomenon with many affective responses, i.e. under this generic term several different effects of persuasive communication are comprised. To give ground to our claims, we provide initial experiments in a machine learning framework to show how various aspects of virality can be predicted according to content features. We further provide a class-based psycholinguistic analysis of the features salient for virality components. © 2011 Springer-Verlag.
CITATION STYLE
Strapparava, C., Guerini, M., & Özbal, G. (2011). Persuasive language and virality in social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6974 LNCS, pp. 357–366). https://doi.org/10.1007/978-3-642-24600-5_39
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