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A novel model for social networks
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A novel model for social networks   (Citations: 4)
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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 which satisfies all the above characteristics is developed. In addition, this model facilitates interaction between various communities. 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 Neighbour of Initial Contact (NIC) as implicit preferential contact, we have considered Neighbour of Neighbour 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.
Conference: Baltic Congress on Future Internet and Communications - BCFIC Riga , 2011
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    • ...The algorithm of the model is as follows [1,2]...
    • ...These three processes lead to following rate equation for the degree of vertex vi [2]...

    Sreedhar Bhukya. Discover Academic Experts in Novel Social Network Model

    • ...we are proposing a contact between the initial contact to its Neighbor of Neighbor contact (tertiary ). The algorithm of the model is as follows [1]: 1) Start with a seed network of N vertices 2) Pick on average mr t 1 random vertex as initial contacts 3) Pick on average ms t 0 neighbors of each initial contact as secondary contact 4) Pick on average mt t 1 neighbors of each secondary contact as tertiary contact 5) Connect the new vertex ...
    • ...These three processes lead to following rate equation for the degree of vertex vi [1]...
    • ...From time evolution of vertex ki (t), we can calculate the degrees of distribution p(k) by forming cumulative distribution F(k) and differentiating with respect to k. Since the mean field approximation[1] the degree ki(t) of a vertex vi increases monotonously from the time ti the vertex initially added to the network, the fraction of vertices whose degree is less than ki(t) at t is equivalent to the fraction of vertices that introduced ...
    • ...These facts lead to the cumulative distribution [1]...
    • ...These three process are described by the rate equation [1] A Social Network Model for Academic Collaboration 207...

    Sreedhar Bhukya. A Social Network Model for Academic Collaboration

    • ...These two aspects we have considered in earlier model [1] and apply earlier model into this Business application...
    • ...The algorithm includes three processes: (1) Random attachment (2) Implicit preferential contact with the neighbors of initial contact (3) In addition to the above we are proposing a contact between the initial contact to its Neighbor of Neighbor contact (tertiary ). The algorithm of the business model is as follows [1], in this model we consider each vertex is as a business person...
    • ...These three processes lead to following rate equation for the degree of vertex vi [1]...
    • ...From time evolution of vertex ki (t), we can calculate the degrees of distribution p(k) by forming cumulative distribution F(k) and differentiating with respect to k. Since the mean field approximation[1,2] the degree ki(t) of a vertex vi increases monotonously from the time ti the vertex initially added to the network, the fraction of vertices whose degree is less than ki(t) at t is equivalent to the fraction of vertices that introduced ...
    • ...These facts lead to the cumulative distribution [1]...
    • ...These three process are described by the rate equation [1]...
    • ...For this equation detail explanation on refer ref [1]...

    Sreedhar Bhukya. A Novel Social Network Model for Business Collaboration

    • ...These two aspects we have considered in earlier model [1] from the earlier model we applied application for research collaboration...
    • ...The algorithm includes three processes: (1) Random attachment (2) Implicit preferential contact with the neighbors of initial contact (3) In addition to the above we are proposing a contact between the initial contact to its Neighbor of Neighbor contact (tertiary ). The algorithm of the model is as follows [1,2] in this paper we consider vertices is as a research person...
    • ...These three processes lead to following rate equation for the degree of vertex vi [1,2]...
    • ...From time evolution of vertex ki (t), we can calculate the degrees of distribution p(k) by forming cumulative distribution F(k) and differentiating with respect to k. Since the mean field approximation[1,2] the degree ki(t) of a vertex vi increases monotonously from the time ti the vertex initially added to the network, the fraction of vertices whose degree is less than ki(t) at t is equivalent to the fraction of vertices that introduced ...
    • ...These facts lead to the cumulative distribution [1]...
    • ...These three process are described by the rate equation [1]...
    • ...For this equation detail explanation on refer ref [1]...

    Sreedhar Bhukya. A Novel Social Network Model for Research Collaboration

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