The potential of grid-side flexibility, the latent ability to reconfigure transmission network topology remains under-used partly because of the lack of empirical studies on how real-world grids evolve.
The connection between humans and the ecology is integrally interconnected and interdependent. The invitation to change our mindset and actions towards the environment, known as ecological conversion, should be emphasized, given the environmental conditions in the present times. Such ideas are reinforced with evangelical texts that can transform humankind for a better tomorrow. This paper explores various aspects of an encyclical named Laudato Si written by Pope Francis. Further, this paper delves into the intricate relationship between spiritual tapestry and environmental concerns by analysing the evangelical text. Laudato Si provides deep insights into humans' challenges as they negotiate their societal and spiritual roles. Pope Francis gives a comprehensive representation of the problems encountered by the world in contemporary times and also puts forward modernism, and also puts forward Christian values and spiritualism as a solution. This research aims to contribute to a better understanding of the changing dynamics of the world, the planet, and the presence of Godliness to cater to environmental challenges.
We introduce the Tidal Tales Plugin, a Firefox extension for efficiently collecting and archiving of Instagram stories, addressing the challenges of ephemeral data in social media research. It enables an automated collection of story metadata and media files without risking account bans. It contributes to Web Science by facilitating expansive, long-term studies with enhanced data access and integrity.
Counts of small subgraphs, or graphlet counts, are widely applicable to measure graph similarity. Computing graphlet counts can be computationally expensive and may pose obstacles in network analysis. We study the role of cliques in graphlet counts as a method for graph similarity in social networks. Higher-order clustering coefficients and the Pivoter algorithm for exact clique counts are employed
In this paper, I explore the potential of network embedding (a.k.a. graph representation learning) to characterize DNS entities in passive network traffic logs. I propose an MF-DNS-E (\underline{M}atrix-\underline{F}actorization-based \underline{DNS} \underline{E}mbedding) method to represent DNS entities (e.g., domain names and IP addresses), where a random-walk-based matrix factorization objective is applied to learn the corresponding low-dimensional embeddings.
Strategic communication in Twitter is compared between different actor groups with regard to the topic of climate change. The main hypothesis is that different actor groups will be more or less central in the reply-trees depending on their strategic interests based on their profession or organizational affiliation.
Anton Tsitsulin, Davide Mottin, Panagiotis Karras
et al.
We introduce a spectral notion of graph complexity derived from the Weyl's law. We experimentally demonstrate its correlation to how well the graph can be embedded in a low-dimensional Euclidean space.
This report gives a brief overview of the origin of social networks and their most popular manifestation in the modern era - the Online Social Networks (OSNs) or social media. It further discusses the positive and negative implications of OSNs on human society. The coupling of Data Science and social media (social media mining) is then put forward as a powerful tool to overcome the current challenges and pave the path for futuristic advancements
Graph-structured data commonly have node annotations. A popular approach for inference and learning involving annotated graphs is to incorporate annotations into a statistical model or algorithm. By contrast, we consider a more direct method named scotch-taping, in which the structural information in a graph and its node annotations are encoded as a factor graph. Specifically, we establish the mathematical basis of this method in the spectral framework.
A continuously evolving geography requires a good understanding in networks. As such, this paper accounts for theories and applications of complex networks and their role both in geography in general, as well as in determining various geographical network trajectories. It assesses how links between agents lead to an evolutionary process of network retention, as well as network variation, and how geography influences these mechanisms.
In this paper we propose and develop a relatively simple and efficient approach for estimating unknown elements of a user-rating matrix in the context of a recommender system (RS). The critical theoretical property of the method is its consistency with respect to arbitrary units implicitly adopted by different users to construct their quantitative ratings of products. It is argued that this property is needed for robust performance accuracy across a broad spectrum of RS application domains.
Political realism aims to describe the interaction of agents involved in struggles for political power. This article formulates realism in terms of quantitative postulates that depict political power as a fluid-like substance flowing through a network of agents. It is shown that agent preferences within this framework resemble those of nation states competing for power. It is suggested that this approach provides a methodology for resolving longstanding debates about realism and a template for interpreting aspects of political behavior more generally.
The PWP map was introduced by the second author as a tool for ranking nodes in networks. In this work we extend this technique so that it can be used to rank links as well. Applying the Girvan-Newman algorithm a ranking method on links induces a deconstruction method for networks, therefore we obtain new methods for finding clustering and core-periphery structures on networks.
The richness of definitions and features of the community-detection problem has led to an impressive body of literature. In fact, many community-detection methods and surveys have been introduced in recent years. The goal here is to present a state-of-the-art of the most mature research in this area. We will therefore concentrate on non-overlapping community detection with the basic graph model. In this chapter we will give an overview of the most influential approaches to community detection that encompass most of the main methods and techniques. A special focus will also be given to community evaluation.
The PWP method was introduced by Diaz in 2009 as a technique for measuring indirect influences in complex networks. It depends on a matrix D, provided by the user, called the matrix of direct influences, and on a positive real parameter which is part of the method itself. We study changes in the method's predictions as D and the parameter vary.
This report presents a very simple algorithm for overlaping community-detection in large graphs under constraints such as the minimum and maximum number of members allowed. The algorithm is based on the simulation of random walks and measures the entropy of each random walk to detect the discovery of a community.
In this paper, we explore the task of gender classification using limited network data with an application to Fotolog. We take a heuristic approach to automating gender inference based on username, followers and network structure. We test our approach on a subset of 100,000 nodes and analyze our results to find that there is a lot of value in these limited information and that there is great promise in further pursuing this approach to classification.
In this paper I'll speak about non-spectral clustering techniques and see how a node ordering based on centrality measures can improve the quality of communities detected. I'll also discuss an improvement to existing techniques, which further improves modularity.
This note argues that when dot-plotting distributions typically found in papers about web and social networks (degree distributions, component-size distributions, etc.), and more generally distributions that have high variability in their tail, an exponentially binned version should always be plotted, too, and suggests Fibonacci binning as a visually appealing, easy-to-use and practical choice.