The Three Dimensions of Social Prominence
One classic problem definition in social network analysis is the study of diffusion 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 influenced nodes, but this approach misses the fact that different scenarios imply different diffusion dynamics, only slightly related to maximizing the number of nodes involved. In this paper we measure three different dimensions of social prominence: the Width, i.e. the ratio of neighbors influenced by a node; the Depth, i.e. the degrees of separation from a node to the nodes perceiving its prominence; and the Strength, i.e. the intensity of the prominence of a node. By defining 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.
KeywordsSocial Network Analysis Closeness Centrality Social Graph Music Genre Revealed Comparative Advantage
Unable to display preview. Download preview PDF.
- 3.Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.P.: Measuring user influence in twitter: The million follower fallacy. In: ICWSM (2010)Google Scholar
- 6.Colizza, V., Barrat, A., Barthelemy, M., Valleron, A.-J., Vespignani, A.: Modeling the worldwide spread of pandemic influenza: Baseline case and containment interventions. PLoS Medicine 4(1), e13 (2007)Google Scholar
- 8.Coscia, M.: Competition and success in the meme pool: a case study on quickmeme.com. In: ICWSM (2013)Google Scholar
- 9.Fowler, J.H., Christakis, N.A.: Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the framingham heart study. Bmj Clinical Research Ed. 337(2), a2338–a2338 (2008)Google Scholar
- 10.Goyal, A., Bonchi, F., Lakshmanan, L.V.S.: Discovering leaders from community actions. In: CIKM, pp. 499–508 (2008)Google Scholar
- 12.Kiang, M.Y., Kumar, A.: A comparative analysis of an extended som network and k-means analysis. Int. J. Know.-Based Intell. Eng. Syst. 8(1), 9–15 (2004)Google Scholar
- 14.Kumar, U.A., Dhamija, Y.: A comparative analysis of som neural network with k-means clustering algorithm. In: Proceedings of IEEE International Conference on Management of Innovation and Technology, pp. 55–59 (2004)Google Scholar