Abstract
A number of recent studies on social networks are based on a characteristic which includes assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model has been developed in the domain of ‘Academic collaboration’ which satisfies all the above characteristics, based on some existing social network models. In addition, this model facilitates interaction between various communities (academic/research groups). This model gives very high clustering coefficient by retaining the asymptotically scale-free degree distribution. Here the community structure is raised from a mixture of random attachment and implicit preferential attachment. In addition to earlier works which only considered Neighbor of Initial Contact (NIC) as implicit preferential contact, we have considered Neighbor of Neighbor of Initial Contact (NNIC) also. This model supports the occurrence of a contact between two Initial contacts if the new vertex chooses more than one initial contacts. This ultimately will develop a complex social network rather than the one that was taken as basic reference.
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References
Bhukya, S.: A novel model for social networks. In: BCFIC, February 16-18, pp. 21–24. IEEE, Los Alamitos (2011)
Toivonen, R., Onnela, J.-P., Saramäki, J., Hyvönen, J., OKaski, K.: A model for social networks. Physica A 371, 851–860 (2006)
Milgram, S.: Psychology Today 2, 60–67 (1967)
Granovetter, M.: The Strength of Weak Ties. Am. J. Soc. 78, 1360–1380 (1973)
Wasserman, S., Faust, K.: Social Network Analysis. Cambridge University Press, Cambridge (1994)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small -world’ networks. Nature 393, 440 (1998)
Newman, M.: The structure of scientific collaboration networks. PNAS 98, 404–409 (2001)
Newman, M.: Coauthorship networks and patterns of scientific collaboration. PNAS 101, 5200–5205 (2004)
Holme, P., Edling, C.R., Liljeros, F.: Structure and Time-Evolution of an Internet Dating Community. Soc. Networks 26, 155–174 (2004)
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA 99, 7821–7826 (2002)
Newman, M.E.J.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)
BarabĂ¡si, A.-L., Albert, R.: Emergence of scaling in random networks. Science 286, 509–512 (1999)
Newman, M.E.J.: Assortative Mixing in Networks. Phys. Rev. Lett. 89, 208–701 (2002)
Newman, M.E.J., Park, J.: Why social networks are different from other t ypes ofnetworks. Phys. Rev. E 68, 036–122 (2003)
Amaral, L.A.N., Scala, A., Barth, M., Stanley, H.E.: Classes of small-world networks. PNAS 97, 11149–11152 (2000)
Boguna, M., Pastor-Satorras, R., DiĂ¡z-Guilera, A., Arenas, A.: Models of social networks based on social distance attachment. Phys. Rev. E 70, 056122 (2004)
Evans, T., Saramäki, J.: Scale-free networks from self-organization. Phys. Rev. E 72, 026138 (2005)
Szabo, G., Alava, M., Kertesz, J.: Structural transitions in scale-free networks. Phys. Rev. EÂ 67, 056102 (2003)
Krapivsky, P.L., Redner, S.: Organization of growing random networks. Phys. Rev. EÂ 63, 066123 (2001)
Sousa, C., Martins, P., Fonseca, B., Paredes, H., Meehan, A., Devine, T.: Social networking system for academic collaboration. In: Luo, Y. (ed.) CDVE 2008. LNCS, vol. 5220, pp. 295–298. Springer, Heidelberg (2008)
Hill, V.A.: Collaboration in an Academic Setting: Does the Network Structure Matter? NSF 07-576 (CASOS)
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Bhukya, S. (2011). A Social Network Model for Academic Collaboration. In: Fong, S. (eds) Networked Digital Technologies. NDT 2011. Communications in Computer and Information Science, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22185-9_18
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DOI: https://doi.org/10.1007/978-3-642-22185-9_18
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