CiteULike: Author Hajra

Modelling aging characteristics in citation networks

Kamalika Hajra — 2008-03-24T22:33:12-00:00

Physica A: Statistical Mechanics and its Applications, Vol. 368, No. 2. (15 August 2006), pp. 575-582.

Growing network models with preferential attachment dependent on both age and degree are proposed to simulate certain features of citation network noted in [Redner, arXiv: physics/0407137 (2004)]. In this directed network, a new node gets attached to an older node with the probability ~K(k)f(t) where the degree and age of the older node are k and t, respectively. Several functional forms of K(k) and f(t) have been considered. The desirable features of the citation network can be reproduced with K(k)~k-[beta] and f(t)~exp([alpha]t) with [beta]=2.0 and [alpha]=-0.2 and with simple modifications in the growth scheme.

Aging in citation networks

Kamalika Hajra — 2007-02-07T22:04:31-00:00

Physica A: Statistical Mechanics and its Applications, Vol. 346, No. 1-2. (1 February 2005), pp. 44-48.

In many growing networks, the age of the nodes plays an important role in deciding the attachment probability of the incoming nodes. For example, in a citation network, very old papers are seldom cited while recent papers are usually cited with high frequency. We study actual citation networks to find out the distribution T(t) of t, the time interval between the published and the cited paper. For different sets of data we find a universal behaviour: T(t)~t-0.9 for t[less-than-or-equals, slant]tc and T(t)~t-2 for t>tc where tc~O(10).

Aging in Citation Networks

Kamalika Hajra — 2006-10-25T21:27:11-00:00

(1 Sep 2004)

In many growing networks, the age of the nodes plays an important role in deciding the attachment probability of the incoming nodes. For example, in a citation network, very old papers are seldom cited while recent papers are usually cited with high frequency. We study actual citation networks to find out the distribution $T(t)$ of $t$, the time interval between the published and the cited paper. For different sets of data we find a universal behaviour: $T(t) ∼ t^-0.9$ for $t ≤ t_c$ and $T(t) ∼ t^-2$ for $t>t_c$ where $t_c ∼ O(10)$.

Phase Transitions in an Aging Network

Kamalika Hajra — 2004-11-22T00:17:30-00:00

(15 June 2004)

We consider a growing network in which an incoming node gets attached to the $i^th$ existing node with the probability $Π_i ∝ k_i^βτ_i^α$, where $k_i$ is the degree of the $i^th$ node and $τ_i$ its present age. The phase diagram in the $α-β$ plane is obtained. The network shows scale-free behaviour, i.e., the degree distribution $P(k) ∼ k^-γ$ with $γ =3$ only along a line in this plane. Small world property, on the other hand, exists over a large region in the phase diagram.

Modelling temporal and spatial features of collaboration network

Anjan Chandra — 2007-02-07T22:05:42-00:00

(7 Dec 2006)

The collaboration network is an example of a social network which has both non-trivial temporal and spatial dependence. Based on the observations of collaborations in Physical Review Letters, a model of collaboration network is proposed which correctly reproduces the time evolution of the link length distributions, clustering coefficients, degree distributions and assortative property of real data to a large extent.

Modelling Aging Characteristics in Citation Networks

Kamalika Hajra — 2006-10-25T21:46:27-00:00

(4 Aug 2005)

Growing network models with preferential attachment dependent on both age and degree are proposed to simulate certain features of citation network noted in \citered2. In this directed network, a new node gets attached to an older node with the probability $∼ K(k)f(t)$ where the degree and age of the older node are $k$ and $t$ respectively. Several functional forms of $K(k)$ and $f(t)$ have been considered. The desirable features of the citation network can be reproduced with $K(k) ∼ k^-β$ and $f(t) ∼ \exp(α t)$ with $β =2.0$ and $α = -0.2$ and with simple modifications in the growth scheme.