Aging in citation networks

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چکیده

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Aging in citation networks

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. ...

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Modelling Aging Characteristics in Citation Networks

Growing network models with preferential attachment dependent on both age and degree are proposed to simulate certain features of citation network noted in [1]. 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...

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Valuing Indirect Citations in Citation Networks using Data Fusion

Any scientific activity requires awareness of previous related activities. Citation networks are the networks in which each document is compared as a link of a chain with its previous and next documents, and the documents with the highest number of citations are considered as the most effective ones in a domain. Most of the introduced methods use direct citations for valuing the documents. One ...

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Drawing Co-Citation Networks of Corona Virus Studies

Background and Aim: The purpose of the present study is to map the coronavirus domain citation network to better understand this domain based on all other citation networks.  Materials and Methods: The present study is applied in terms of purpose, and is descriptive scientometrics in terms of type, which has been done with the all-citation method. In this study, all scientific publications on ...

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Link prediction in citation networks

In this article, we build models to predict the existence of citations among papers by formulating link prediction for 5 large-scale datasets of citation networks. The supervised machine-learning model is applied with 11 features. As a result, our learner performs very well, with the F1 values of between 0.74 and 0.82. Three features in particular, link-based Jaccard coefficient , difference in...

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ژورنال

عنوان ژورنال: Physica A: Statistical Mechanics and its Applications

سال: 2005

ISSN: 0378-4371

DOI: 10.1016/j.physa.2004.08.048