Social Network Analysis with sna

Modern social network analysis---the analysis of relational data arising from social systems---is a computationally intensive area of research. Here, we provide an overview of a software package which provides support for a range of network analytic functionality within the R statistical computing environment. General categories of currently supported functionality are described, and brief examples of package syntax and usage are shown.

Moment-Based Spectral Analysis of Random Graphs with Given Expected Degrees

In this paper, we analyze the limiting spectral distribution of the adjacency matrix of a random graph ensemble, proposed by Chung and Lu, in which a given expected degree sequence $\overline{w}_n^{^{T}} = (w^{(n)}_1,\ldots,w^{(n)}_n)$ is prescribed on the ensemble. Let $\mathbf{a}_{i,j} =1$ if there is an edge between the nodes $\{i,j\}$ and zero otherwise, and consider the normalized random adjacency matrix of the graph ensemble: $\mathbf{A}_n$ $=$ $[\mathbf{a}_{i,j}/\sqrt{n}]_{i,j=1}^{n}$. The empirical spectral distribution of $\mathbf{A}_n$ denoted by $\mathbf{F}_n(\mathord{\cdot})$ is the empirical measure putting a mass $1/n$ at each of the $n$ real eigenvalues of the symmetric matrix $\mathbf{A}_n$. Under some technical conditions on the expected degree sequence, we show that with probability one, $\mathbf{F}_n(\mathord{\cdot})$ converges weakly to a deterministic distribution $F(\mathord{\cdot})$. Furthermore, we fully characterize this distribution by providing explicit expressions for the moments of $F(\mathord{\cdot})$. We apply our results to well-known degree distributions, such as power-law and exponential. The asymptotic expressions of the spectral moments in each case provide significant insights about the bulk behavior of the eigenvalue spectrum

Small Worlds in Networks of Inventors and the Role of Science: An Analysis of France.

· Using data on patent applications at European Patent Office, we examine the structural properties of networks of inventors in France in different technologies, and how they depend from the inventive activity of scientists from universities and public research organizations (PROs). We revisit earlier findings on small world properties of social networks of inventors, and propose more rigorous tests of such hypothesis. We find that academic and PRO inventors contribute significantly to patenting in science‐based fields. Such contribution is decisive for the emergence of small world properties.networks, inventors, academic patenting, small world.

Possibilities of using graphical and numerical tools in the exposition of process capability assessment techniques

Purpose: The paper focuses on how the problem of process capability assessment can be handled when taught, using convenient numerical and graphical means. The contents of the paper results from the authors' own academic and practical experience, which suggested that many important steps are overlooked in the process of selecting and using capability indices. Methodology/Approach: Selected problems in capability assessment are illustrated with suitable examples and graphs. Findings: The authors' experience is reflected in the paper, aiming to emphasize what matters and how, and what does not. Also, a new capability index is introduced. Research Limitation/implication: The style in which the problems are analysed may serve as a guide for further studies in the field and capability index applications. Originality/Value of paper: The paper also contains, aside from specific examples, some more advanced techniques, and is therefore accompanied by software readouts, since computer support is required in such cases. Category: Conceptual paperWeb of Science232331

Towards realistic artificial benchmark for community detection algorithms evaluation

Assessing the partitioning performance of community detection algorithms is one of the most important issues in complex network analysis. Artificially generated networks are often used as benchmarks for this purpose. However, previous studies showed their level of realism have a significant effect on the algorithms performance. In this study, we adopt a thorough experimental approach to tackle this problem and investigate this effect. To assess the level of realism, we use consensual network topological properties. Based on the LFR method, the most realistic generative method to date, we propose two alternative random models to replace the Configuration Model originally used in this algorithm, in order to increase its realism. Experimental results show both modifications allow generating collections of community-structured artificial networks whose topological properties are closer to those encountered in real-world networks. Moreover, the results obtained with eleven popular community identification algorithms on these benchmarks show their performance decrease on more realistic networks

A Network Topology Approach to Bot Classification

Automated social agents, or bots, are increasingly becoming a problem on social media platforms. There is a growing body of literature and multiple tools to aid in the detection of such agents on online social networking platforms. We propose that the social network topology of a user would be sufficient to determine whether the user is a automated agent or a human. To test this, we use a publicly available dataset containing users on Twitter labelled as either automated social agent or human. Using an unsupervised machine learning approach, we obtain a detection accuracy rate of 70%

Effects of decentralization on school resources

Sweden has undertaken major national reforms of its schooling sector which, consequently, has been classified as one of the most decentralized ones in the OECD. This paper investigates the extent to which local tax base, grants, preferences and structural characteristics affected local schooling resources as decentralization took place. We use municipal data for the period 1989–95 which covers the key reform years without confounding decentralization with institutional changes after 1995. The main arguments against decentralization are not supported by our findings. First, school spending as well as teacher density is found to be more equally distributed across municipalities following decentralization. Second, local tax capacity does not influence schooling resources more in the decentralized regime than in the centralized regime. We also find that the form in which grants are distributed matter: Targeted grants have a significant positive impact on resources while general grants have not.School resources; school finance reform; decentralization