Abstract
Information usually spreads between people by the mean of textual documents. During such propagation, a piece of information can either remain the same or mutate. We propose to formulate information spread with a set of time-ordered document chains along which some information has likely been transmitted. This formulation is different from the usual graph view of a transmission process as it integrates a notion of lineage of the information. We also propose a way to construct a candidate set of document chains for the information propagation in a corpus of documents. We show that most of the chains have been judged as plausible by human experts.
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The full dataset can be obtained at: https://aminer.org/citation.
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Huyghues-Despointes, C., Khouas, L., Velcin, J., Loudcher, S. (2019). Weaving Information Propagation: Modeling the Way Information Spreads in Document Collections. In: Meurs, MJ., Rudzicz, F. (eds) Advances in Artificial Intelligence. Canadian AI 2019. Lecture Notes in Computer Science(), vol 11489. Springer, Cham. https://doi.org/10.1007/978-3-030-18305-9_35
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DOI: https://doi.org/10.1007/978-3-030-18305-9_35
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