Abstract
It is quite important in ITeS to consider phenomena and behavior of people on social networks. In this chapter, we discuss information diffusion and dissipative effect using analytical and computational methods in order to investigate the phenomena and behavior. In general, network structure plays an essential role in the process of information diffusion so that we are faced by the difficulties in control our personal and confidential information. The computer simulation in this chapter assumes a scale-free network as often seen in online social networks. We find out that the process of information diffusion obeys a certain curve and that there may be quantum leaps which are caused by the hubs of social networks. Adding to this, we have obtained the results of dissipative effect using two operations. One eliminates the main hub from the networks, the other reconstructs the network as a stochastic network based on a constant diffusion probability. Moreover, we obtain the suggestion of information diffusion and dissipative effect for the further investigation in information management and malware infection in information security.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74(1):47–97
Aral S, Brynjolfsson E, Alstyne MWV (2007) Productivity effects of information diffusion in networks. MIT Center for Digital Business, Working Paper #234
Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512
Cardanobile S (2010) Diffusion systems and heat equations on networks. Suedawestdeutscher Verlag Fuer, Hochschulschrif
Dan Y (2011a) Modeling and simulation of diffusion phenomena on social networks. IEEE Proc ICCMS 1:139–146
Dan Y (2011b) Mathematical analysis and simulation of information diffusion on networks. SAINT 2011 Workshop: IT enabled Services (ITeS), pp 550–555
Dellarocas C (2003) The digitization of word of mouth: promise and challenges of online feedback mechanisms. Manage Sci 49(10):1407–1424
Dorogovtsev SN, Mendes JFF, Samukhin AN (2000) Structure of growing networks with preferential linking. Phys Rev Lett 85:4633–4636
Huckfeldt R, Sprague J (1991) Discussant effect on vote choice: intimacy, structure and interdependence. J Polit 53(1):122–158
Kullmann L, Kertész J (2001) Preferencial growth: exact solution of the time dependent distributions. Phys Rev E, 63(051112)
Leskovec J, Adamic L, Huberman BA (2007) The dynamics of viral marketing. ACM Trans Web 1(1), Article No. 5
Milgram S (1967) The small world problem. Psychol Today 1(1):60–67
Newman MEJ (2010) Networks. Oxford University Press, Oxford
Newman MEJ, Barabási A-L, Watts DJ (2006) The structure and dynamics of networks. Princeton University Press, Princeton
Nikoloski Z, Deo N, Kucera L (2006) Correlation model of worm propagation on scale-free networks. Complexus 3:169–182
Orita A (2008) Users attitude towards anonymous and real-name services on the internet in Japan In: JPAIS session at international conference on computer and information science (ICIS), Paris
Page L, Brin S, Motwani R,Winograd T (1999) The PageRank citation ranking: bringing order to the web. Technical Report, Stanford InfoLab
Quing S, Wen W (2005) A survey and trends on internet worms. Comput Secur 24:334–346
Rogers EM (2003) Diffusion of innovations, 5th edn. Free Press, New York
V´azquez A, Pastor-Satorras R,Vespignani A (2002) Large-scale topological and dynamical propertes of the internet. Phys Rev E 65(066130)
Verhulst P-F (1838) Notice sur la loi que la population poursuit dans son accroissement. Correspondance mathématique et physique 10:113–121
Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, Cambridge
Watts D (2003) Six degrees: the science of a connected age. W.W. Norton, New York
Watts DJ, Strogatz SZ (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Wien
About this chapter
Cite this chapter
Dan, Y. (2013). Information Diffusion and Dissipative Effect on Social Networks. In: Uesugi, S. (eds) IT Enabled Services. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1425-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-7091-1425-4_3
Published:
Publisher Name: Springer, Vienna
Print ISBN: 978-3-7091-1424-7
Online ISBN: 978-3-7091-1425-4
eBook Packages: Computer ScienceComputer Science (R0)