Abstract
This work proposes a framework to study the propagation of individual interests in scientific social networks. We analyze the domain of computer science and we profile members of the social network by means of semantic techniques. We model the evolution of interests as a diffusion process and we measure individual features, such as members’ susceptibilities and authorities. The DBLP (Digital Bibliography and Library Project) dataset has been selected as main source since it provides an extensive list of scientific publications in this field.
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Acknowledgments
The authors are indebted to Fulvio D’Antonio for providing the preliminary set of topics. Salvatore Tucci, Emiliano Casalicchio, and Francesco Lo Presti are kindly acknowledged for stimulating discussions.
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D’Agostino, G., De Nicola, A. (2016). Interests Propagation in Computer Science Research Community. In: Battiston, S., De Pellegrini, F., Caldarelli, G., Merelli, E. (eds) Proceedings of ECCS 2014. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-29228-1_12
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DOI: https://doi.org/10.1007/978-3-319-29228-1_12
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