Pennacchioli D., Rossetti G., Pappalardo L., Pedreschi D., Giannotti F., Coscia M.
H.2.8 Database applications Complex networks Data mining Community discovery
One classic problem denition in social network analysis is the study of diusion in networks, which enables us to tackle problems like favoring the adoption of positive technologies. Most of the attention has been turned to how to maximize the number of in uenced nodes, but this approach misses the fact that dierent scenarios imply dierent dif- fusion dynamics, only slightly related to maximizing the number of nodes involved. In this paper we measure three dierent dimensions of social prominence: the Width, i.e. the ratio of neighbors in uenced by a node; the Depth, i.e. the degrees of separation from a node to the nodes perceiv- ing its prominence; and the Strength, i.e. the intensity of the prominence of a node. By dening a procedure to extract prominent users in complex networks, we detect associations between the three dimensions of social prominence and classical network statistics. We validate our results on a social network extracted from the Last.Fm music platform.
Source: SocInfo2013 - Social Informatics. 5th International Conference, pp. 319–332, Kyoto, Japan, 25-27 November 2013
@inproceedings{oai:it.cnr:prodotti:277769, title = {The three dimensions of social prominence}, author = {Pennacchioli D. and Rossetti G. and Pappalardo L. and Pedreschi D. and Giannotti F. and Coscia M.}, doi = {10.1007/978-3-319-03260-3_28}, booktitle = {SocInfo2013 - Social Informatics. 5th International Conference, pp. 319–332, Kyoto, Japan, 25-27 November 2013}, year = {2013} }