Related papers: Applying centrality measures to impact analysis: A…
Centrality metrics play a crucial role in network analysis, while the choice of specific measures significantly influences the accuracy of conclusions as each measure represents a unique concept of node importance. Among over 400 proposed…
In this paper, we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000 to 2016 from a network analytical perspective. We focus on the papers presented at the…
To measure node importance, network scientists employ centrality scores that typically take a microscopic or macroscopic perspective, relying on node features or global network structure. However, traditional centrality measures such as…
In complex networks a common task is to identify the most important or "central" nodes. There are several definitions, often called centrality measures, which often lead to different results. Here we study extensively correlations between…
Centrality is an important notion in complex networks; it could be used to characterize how influential a node or an edge is in the network. It plays an important role in several other network analysis tools including community detection.…
Most people simultaneously belong to several distinct social networks, in which their relations can be different. They have opinions about certain topics, which they share and spread on these networks, and are influenced by the opinions of…
It is hard to detect important articles in a specific context. Information retrieval techniques based on full text search can be inaccurate to identify main topics and they are not able to provide an indication about the importance of the…
In growing numbers, scholars are integrating social media tools like blogs, Twitter, and Mendeley into their professional communications. The online, public nature of these tools exposes and reifies scholarly processes once hidden and…
The launching of Scopus and Google Scholar, and methodological developments in Social Network Analysis have made many more indicators for evaluating journals available than the traditional Impact Factor, Cited Half-life, and Immediacy Index…
Demographic and behavioral characteristics of journal authors are important indicators of homophily in co-authorship networks. In the presence of correlations between adjacent nodes (assortative mixing), combining the estimation of the…
Nestedness is a property of interaction networks widely observed in natural mutualistic communities. Despite a widespread interest on this pattern, no general consensus exists on how to measure it. Instead, several metrics aiming at…
The current research conducts a comprehensive analysis of citation networks focusing on publications by authors affiliated with Egyptian institutions. Leveraging the Semantic Scholar platform and its API, a citation network and a…
Citation metrics are analytic measures used to evaluate the usage, impact and dissemination of scientific research. Traditionally, citation metrics have been independently measured at each level of the publication pyramid, namely at the…
Identifying influential nodes in a network is a fundamental issue due to its wide applications, such as accelerating information diffusion or halting virus spreading. Many measures based on the network topology have emerged over the years…
We examine two-layer networks and centrality measures defined on them. We propose two fast and accurate algorithms to approximate the game-theoretic centrality measures and examine connection between centrality measures and characteristics…
Citation metrics are becoming pervasive in the quantitative evaluation of scholars, journals and institutions. More then ever before, hiring, promotion, and funding decisions rely on a variety of impact metrics that cannot disentangle…
We perform the first axiomatic analysis of medial centrality measures. These measures, also called betweenness-like centralities, assess the role of a node in connecting others in the network. We focus on a setting with one target node and…
The identification of the most influential spreaders in networks is important to control and understand the spreading capabilities of the system as well as to ensure an efficient information diffusion such as in rumor-like dynamics. Recent…
Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures…
Journal Impact Factor is a popular metric for determining the quality of a journal in academia. The number of citations received by a journal is a crucial factor in determining the impact factor, which may be misused in multiple ways.…