Abstract
Online social network platforms have served as a substantial venue for research, offering a plethora of data that can be analysed to cultivate insights about the way humans behave and interact within the virtual borders of these platforms. In addition to generating content, these platforms provide the means to spread content via built-in functionalities. The traces of the spreading content and the individuals’ incentives behind such behaviour are all parts of a phenomenon known as information diffusion. This phenomenon has been extensively studied in the literature from different perspectives, one of which is cascades: the traces of the spreading content. These traces form structures that link users to each other, where these links represent the direction of information flow between the users. In fact, cascades have served as an artefact to study the information diffusion processes on online social networks. In this paper, we present a survey of cascades; we consider their definitions and significance. We then look into their topology and what information is used to construct them and how the type of content and the platform can consequently affect cascades’ networks. Additionally, we present a survey of the structural and temporal features of cascades; we categorise them, define them and explain their significance, as these features serve as quantifiers to understand and overcome the complex nature of cascades.
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Alrajebah, N., Tiropanis, T., Carr, L. (2017). Cascades on Online Social Networks: A Chronological Account. In: Kompatsiaris, I., et al. Internet Science. INSCI 2017. Lecture Notes in Computer Science(), vol 10673. Springer, Cham. https://doi.org/10.1007/978-3-319-70284-1_31
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