Related papers: Network Community Detection: A Review and Visual S…
Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly-connected groups…
Many real systems have been modelled in terms of network concepts, and written texts are a particular example of information networks. In recent years, the use of network methods to analyze language has allowed the discovery of several…
Networks built to model real world phenomena are characeterised by some properties that have attracted the attention of the scientific community: (i) they are organised according to community structure and (ii) their structure evolves with…
Community detection is a fundamental problem in social network analysis consisting in unsupervised dividing social actors (nodes in a social graph) with certain social connections (edges in a social graph) into densely knitted and highly…
A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in network analysis. Despite the classical spectral clustering…
Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network.…
Community structure analysis is a powerful tool for social networks, which can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained…
Co-authorship graphs (that is, the graph of authors linked by co-authorship of papers) are complex networks, which expresses the dynamics of a complex system. Only recently its study has started to draw interest from the EC community, the…
How does the collaboration network of researchers coalesce around a scientific topic? What sort of social restructuring occurs as a new field develops? Previous empirical explorations of these questions have examined the evolution of…
In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is…
The number of scientific publications continues to rise exponentially, especially in Computer Science (CS). However, current solutions to analyze those publications restrict access behind a paywall, offer no features for visual analysis,…
The analysis of complex networks permeates all sciences, from biology to sociology. A fundamental, unsolved problem is how to characterize the community structure of a network. Here, using both standard and novel benchmarks, we show that…
In recent era, networks of data are growing massively and forming a shape of complex structure. Data scientists try to analyze different complex networks and utilize these networks to understand the complex structure of a network in a…
Citations between scientific papers and related bibliometric indices, such as the $h$-index for authors and the impact factor for journals, are being increasingly used - often in controversial ways - as quantitative tools for research…
A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with…
Digitization of publications, advancement in communication technology, and the availability of bibliographic data have made it easier for the researchers to study the growth and dynamics of any discipline. We present a study on…
Community analysis is an important way to ascertain whether or not a complex system consists of sub-structures with different properties. In this paper, we give a two level community structure analysis for the SSCI journal system by most…
In network science complex systems are represented as a mathematical graphs consisting of a set of nodes representing the components and a set of edges representing their interactions. The framework of networks has led to significant…
We use a technique recently developed by Blondel et al. (2008) in order to detect scientific specialties from author cocitation networks. This algorithm has distinct advantages over most of the previous methods used to obtain cocitation…
To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network…