Latest in cs.si

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Analysis of the Wikipedia Network of MathematiciansFeb 20 2019Feb 21 2019We look at the network of mathematicians defined by the hyperlinks between their biographies on Wikipedia. We show how to extract this information using three snapshots of the Wikipedia data, taken in 2013, 2017 and 2018. We illustrate how such Wikipedia ... More
Graph Neural Networks for Social RecommendationFeb 19 2019In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph data. These advantages of GNNs provide great potential to advance social ... More
Do zealots increase or decrease the polarization in social networks?Feb 19 2019Zealots are the nodes in a social network who do not change their opinions under social pressure, and have been considered crucial in the study of opinion dynamics on complex networks. Here we show that whether or not their presence affects the social ... More
A Broad Evaluation of the Tor English Content EcosystemFeb 18 2019Tor is among most well-known dark net in the world. It has noble uses, including as a platform for free speech and information dissemination under the guise of true anonymity, but may be culturally better known as a conduit for criminal activity and as ... More
The Ambivalence of Cultural Homophily: Field Positions, Semantic Similarities, and Social Network Ties in Creative CollectivesFeb 18 2019This paper utilizes a mixture of qualitative, formal, and statistical socio-semantic network analyses to examine how cultural homophily works when field logic meets practice. On the one hand, because individuals in similar field positions are also imposed ... More
Quality of Life Assessment of Diabetic patients from health-related blogsFeb 18 2019Motivations: People are generating an enormous amount of social data to describe their health care experiences, and continuously search information about diseases, symptoms, diagnoses, doctors, treatment options and medicines. The increasing availability ... More
Twitch Plays Pokemon, Machine Learns Twitch: Unsupervised Context-Aware Anomaly Detection for Identifying Trolls in Streaming DataFeb 17 2019With the increasing importance of online communities, discussion forums, and customer reviews, Internet "trolls" have proliferated thereby making it difficult for information seekers to find relevant and correct information. In this paper, we consider ... More
Collaborative Similarity Embedding for Recommender SystemsFeb 17 2019We present collaborative similarity embedding (CSE), a unified framework that exploits comprehensive collaborative relations available in a user-item bipartite graph for representation learning and recommendation. In the proposed framework, we differentiate ... More
Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?Feb 16 2019The proliferation of smart mobile devices has spurred an explosive growth of mobile crowd-learning services, where service providers rely on the user community to voluntarily collect, report, and share real-time information for a collection of scattered ... More
Statistical properties of user activity fluctuations in virtual worldsFeb 16 2019User activity fluctuations reflect the performance of online society. We investigate the statistical properties of 1-min user activity time series of simultaneously online users inhabited in 95 independent virtual worlds. The number of online users exhibits ... More
CruzAffect at AffCon 2019 Shared Task: A feature-rich approach to characterize happinessFeb 16 2019We present our system, CruzAffect, for the CL-Aff Shared Task 2019. CruzAffect consists of several types of robust and efficient models for affective classification tasks. We utilize both traditional classifiers, such as XGBoosted Forest, as well as a ... More
Replications in quantitative and qualitative methods: a new era for commensurable digital social sciencesFeb 15 2019Social sciences were built from comparison methods assembling field works and data, either quantitative or qualitative. Big Data offers new opportunities to extend this requirement to build commensurable data sets. The paper tells the story of the two ... More
Learning Topological Representation for Networks via Hierarchical SamplingFeb 15 2019The topological information is essential for studying the relationship between nodes in a network. Recently, Network Representation Learning (NRL), which projects a network into a low-dimensional vector space, has been shown their advantages in analyzing ... More
When Celebrities Speak: A Nationwide Twitter Experiment Promoting Vaccination in IndonesiaFeb 15 2019Celebrity endorsements are often sought to influence public opinion. We ask whether celebrity endorsement per se has an effect beyond the fact that their statements are seen by many, and whether on net their statements actually lead people to change their ... More
Finding Nearest Neighbors in graphs locallyFeb 14 2019Many distributed learning techniques have been motivated by the increasing size of datasets and their inability to fit into main memory on a single machine. We propose an algorithm that finds the nearest neighbor in a graph locally without the need of ... More
Using Key Player Analysis as a Method for Examining the Role of Community Animators in Technology AdoptionFeb 14 2019This paper examines the role of community animators in technology adoption. Community animators are individuals that actively build social networks and broker ties between nodes in those networks. The present study observes technology adoption patterns ... More
Network Semantic Segmentation with Application to GitHubFeb 14 2019In this paper we introduce the concept of network semantic segmentation for social network analysis. We consider the GitHub social coding network which has been a center of attention for both researchers and software developers. Network semantic segmentation ... More
Regional economic status inference from information flow and talent mobilityFeb 14 2019Novel data has been leveraged to estimate socioeconomic status in a timely manner, however, direct comparison on the use of social relations and talent movements remains rare. In this letter, we estimate the regional economic status based on the structural ... More
A Cross-Repository Model for Predicting Popularity in GitHubFeb 14 2019Social coding platforms, such as GitHub, can serve as natural laboratories for studying the diffusion of innovation through tracking the pattern of code adoption by programmers. This paper focuses on the problem of predicting the popularity of software ... More
SoK: Transparent Dishonesty: front-running attacks on BlockchainFeb 13 2019We consider front-running to be a course of action where an entity benefits from prior access to privileged market information about upcoming transactions and trades. Front-running has been an issue in financial instrument markets since the 1970s. With ... More
Sampling networks by nodal attributesFeb 13 2019In a social network the individuals or nodes connect to other nodes by choosing one of the channels of communication at a time to re-establish the existing social links. Since information for research is usually restricted to a limited number of channels ... More
Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters in the world economyFeb 12 2019Groups of firms often achieve a competitive advantage through the formation of geo-industrial clusters. Although many exemplary clusters, such as Hollywood or Silicon Valley, have been frequently studied, systematic approaches to identify and analyze ... More
Spectra of networks containing short loopsFeb 12 2019The spectrum of the adjacency matrix plays several important roles in the mathematical theory of networks and in network data analysis, for example in percolation theory, community detection, centrality measures, and the theory of dynamical systems on ... More
A Probabilistic Framework to Node-level Anomaly Detection in Communication NetworksFeb 12 2019In this paper we consider the task of detecting abnormal communication volume occurring at node-level in communication networks. The signal of the communication activity is modeled by means of a clique stream: each occurring communication event is instantaneous ... More
Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market PerformanceFeb 12 2019The production and consumption of information about Bitcoin and other digital-, or 'crypto'-, currencies have grown together with their market capitalisation. However, a systemic investigation of the relationship between online attention and market dynamics, ... More
RTbust: Exploiting Temporal Patterns for Botnet Detection on TwitterFeb 12 2019Within OSNs, many of our supposedly online friends may instead be fake accounts called social bots, part of large groups that purposely re-share targeted content. Here, we study retweeting behaviors on Twitter, with the ultimate goal of detecting retweeting ... More
An Analysis of United States Online Political Advertising TransparencyFeb 12 2019During the summer of 2018, Facebook, Google, and Twitter created policies and implemented transparent archives that include U.S. political advertisements which ran on their platforms. Through our analysis of over 1.3 million ads with political content, ... More
WikiLinkGraphs: A complete, longitudinal and multi-language dataset of the Wikipedia link networksFeb 12 2019Wikipedia articles contain multiple links connecting a subject to other pages of the encyclopedia. In Wikipedia parlance, these links are called internal links or wikilinks. We present a complete dataset of the network of internal Wikipedia links for ... More
Asymptotic resolution bounds of generalized modularity and statistically significant community detectionFeb 12 2019The maximization of generalized modularity performs well on networks in which the members of all communities are statistically indistinguishable from each other. However, there is no theory defining the maximization performance in more realistic networks ... More
Meta Diagram based Active Social Networks AlignmentFeb 12 2019Network alignment aims at inferring a set of anchor links matching the shared entities between different information networks, which has become a prerequisite step for effective fusion of multiple information networks. In this paper, we will study the ... More
Data-driven unsupervised clustering of online learner behaviourFeb 11 2019The widespread adoption of online courses opens opportunities for the analysis of learner behaviour and for the optimisation of web-based material adapted to observed usage. Here we introduce a mathematical framework for the analysis of time series collected ... More
Fast consensus clustering in complex networksFeb 11 2019Algorithms for community detection are usually stochastic, leading to different partitions for different choices of random seeds. Consensus clustering has proven to be an effective technique to derive more stable and accurate partitions than the ones ... More
Reconstructing dynamical networks via feature rankingFeb 11 2019Empirical data on real complex systems are becoming increasingly available. Parallel to this is the need for new methods of reconstructing (inferring) the topology of networks from time-resolved observations of their node-dynamics. The methods based on ... More
A Reputation System for Marketplaces - Viability AssessmentFeb 11 2019In this work we explore the implementation of the reputation system for a generic marketplace, describe details of the algorithm and parameters driving its operation, justify an approach to simulation modeling, and explore how various kinds of reputation ... More
Stratified communities in complex business networksFeb 11 2019This paper presents a new definition of the community structure of a network, which takes also into account how communities are stratified. In particular, we extend the standard concept of clustering coefficient and provide the local $l$-adjacency clustering ... More
Fake News Detection on Social Media using Geometric Deep LearningFeb 10 2019Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the cost of dubious trustworthiness and significant risk of exposure to 'fake ... More
Identifying Fake News from Twitter Sharing Data: A Large-Scale StudyFeb 10 2019Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applied to a large and statistically significant portion of the news that are ... More
Multi-choice opinion dynamics model based on Latane theoryFeb 09 2019In this paper Nowak--Szamrej-Latan\'e model is reconsidered. This computerised model of opinion formation bases on Latan\'e theory of social impact. We modify this model to allow for multi (more than two) opinions. With computer simulations we show that ... More
Synergistic Effects in Networked Epidemic Spreading DynamicsFeb 08 2019In this brief, we study epidemic spreading dynamics taking place in complex networks. We specifically investigate the effect of synergy, where multiple interactions between nodes result in a combined effect larger than the simple sum of their separate ... More
A Novel Graph Analytic Approach to Monitor Terrorist NetworksFeb 07 2019Terrorist attacks all across the world have become a major source of concern for almost all national governments. The United States Department of State's Bureau of Counter-Terrorism, maintains a list of 66 terrorist organizations spanning the entire world. ... More
Red Bots Do It Better Comparative Analysis of Social Bot Partisan BehaviorFeb 07 2019Recent research brought awareness of the issue of bots on social media and the significant risks of mass manipulation of public opinion in the context of political discussion. In this work, we leverage Twitter to study the discourse during the 2018 US ... More
Red Bots Do It Better: Comparative Analysis of Social Bot Partisan BehaviorFeb 07 2019Feb 08 2019Recent research brought awareness of the issue of bots on social media and the significant risks of mass manipulation of public opinion in the context of political discussion. In this work, we leverage Twitter to study the discourse during the 2018 US ... More
A Network-centric Framework for Auditing Recommendation SystemsFeb 07 2019To improve the experience of consumers, all social media, commerce and entertainment sites deploy Recommendation Systems (RSs) that aim to help users locate interesting content. These RSs are black-boxes - the way a chunk of information is filtered out ... More
Anti-modular nature of partially bipartite networks makes them infra small-worldFeb 07 2019Strong inter-dependence in complex systems can manifest as partially bipartite networks characterized by interactions occurring primarily between distinct groups of nodes (identified as modules). In this paper, we show that the anti-modular character ... More
Heterogeneous Edge Embeddings for Friend RecommendationFeb 07 2019We propose a friend recommendation system (an application of link prediction) using edge embeddings on social networks. Most real-world social networks are multi-graphs, where different kinds of relationships (e.g. chat, friendship) are possible between ... More
Modeling and Analysis of Tagging Networks in Stack Exchange CommunitiesFeb 06 2019Large Question-and-Answer (Q&A) platforms support diverse knowledge curation on the Web. While researchers have studied user behavior on the platforms in a variety of contexts, there is relatively little insight into important by-products of user behavior ... More
Hawkes Process for Understanding the Influence of Pathogenic Social Media AccountsFeb 05 2019Over the past years, political events and public opinion on the Web have been allegedly manipulated by accounts dedicated to spreading disinformation and performing malicious activities on social media. These accounts hereafter referred to as "Pathogenic ... More
Inferring the strength of social ties: a community-driven approachFeb 05 2019Online social networks are growing and becoming denser. The social connections of a given person may have very high variability: from close friends and relatives to acquaintances to people who hardly know. Inferring the strength of social ties is an important ... More
Detecting Permanent and Intermittent Purchase Hotspots via Computational StigmergyFeb 05 2019The analysis of credit card transactions allows gaining new insights into the spending occurrences and mobility behavior of large numbers of individuals at an unprecedented scale. However, unfolding such spatiotemporal patterns at a community level implies ... More
Animated Drag and Drop Interaction for Dynamic Multidimensional GraphsFeb 05 2019In this paper, we propose a new drag and drop interaction technique for graphs. We designed this interaction to support analysis in complex multidimensional and temporal graphs. The drag and drop interaction is enhanced with an intuitive and controllable ... More
High-resolution home location prediction from tweets using deep learning with dynamic structureFeb 03 2019High-resolution prediction of the home location of people has applications in diverse fields, including agriculture, transportation, and public health. The goal here is to obtain an accurate estimate of home locations of a sufficiently large subset of ... More
Error-Correcting Decoders for Communities in NetworksFeb 03 2019As recent work demonstrated, the task of identifying communities in networks can be considered analogous to the classical problem of decoding messages transmitted along a noisy channel. We leverage this analogy to develop a community detection method ... More
How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing StyleFeb 02 2019Rapid development of Internet technologies promotes traditional newspapers to report news on social networks. However, people on social networks may have different needs which naturally arises the question: whether can we analyze the influence of writing ... More
Anomaly detection in complex networks as a diagnosis of model over-simplificationFeb 02 2019Tremendous advances have been made in our understanding of the properties and evolution of complex networks. These advances were initially driven by information-poor empirical networks and theoretical analysis of unweighted and undirected graphs. Recently, ... More
Polarization and Fluctuations in Signed Social NetworksFeb 02 2019Social networks are composed of individuals with a variety of friendly and antagonistic relationships. There has been an increasing interest in the modeling and analysis of how opinions spread as a function of these relationships. In this paper, we propose ... More
A model for meme popularity growth in social networking systems based on biological principle and human interest dynamicsFeb 01 2019We analyze five big data sets from a variety of online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors. For example, there is linear growth associated with online recommendation ... More
StaTIX - Statistical Type Inference on Linked DataFeb 01 2019Large knowledge bases typically contain data adhering to various schemas with incomplete and/or noisy type information. This seriously complicates further integration and post-processing efforts, as type information is crucial in correctly handling the ... More
A surface-depth theory of the emergence of complex networksFeb 01 2019The broadly general characteristics of complex networks found across disciplines-- such as high clustering coefficients and heavy-tailed degree distributions-- has long invited the question of whether there are general generating mechanisms behind them. ... More
Non-Markovian Monte Carlo on Directed GraphsFeb 01 2019Markov Chain Monte Carlo (MCMC) has been the de facto technique for sampling and inference of large graphs such as online social networks. At the heart of MCMC lies the ability to construct an ergodic Markov chain that attains any given stationary distribution ... More
Social Network Based Substance Abuse Prevention via Network Modification (A Preliminary Study)Feb 01 2019Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of preventing and reducing substance abuse. While effective, unfortunately, inappropriate intervention groups ... More
Perils and Challenges of Social Media and Election Manipulation Analysis: The 2018 US MidtermsJan 31 2019One of the hallmarks of a free and fair society is the ability to conduct a peaceful and seamless transfer of power from one leader to another. Democratically, this is measured in a citizen population's trust in the electoral system of choosing a representative ... More
Predictability of missing links in complex networksJan 31 2019Predicting missing links in real networks is an important problem in network science to which considerable efforts have been devoted, giving as a result a vast plethora of link prediction methods in the literature. In this work, we take a different point ... More
A large-scale crowdsourced analysis of abuse against women journalists and politicians on TwitterJan 31 2019We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully curate an unbiased ... More
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global PovertyJan 31 2019With the rapid expansion of mobile phone networks in developing countries, large-scale graph machine learning has gained sudden relevance in the study of global poverty. Recent applications range from humanitarian response and poverty estimation to urban ... More
Beyond the clustering coefficient: A topological analysis of node neighbourhoods in complex networksJan 30 2019In Network Science node neighbourhoods, also called ego-centered networks have attracted large attention. In particular the clustering coefficient has been extensively used to measure their local cohesiveness. In this paper, we show how, given two nodes ... More
Twitter Job/Employment Corpus: A Dataset of Job-Related Discourse Built with Humans in the LoopJan 30 2019We present the Twitter Job/Employment Corpus, a collection of tweets annotated by a humans-in-the-loop supervised learning framework that integrates crowdsourcing contributions and expertise on the local community and employment environment. Previous ... More
A semi-supervised approach to message stance classificationJan 29 2019Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active ... More
Persistent Homology of Geospatial Data: A Case Study with VotingJan 29 2019A crucial step in the analysis of persistent homology is transformation of data into a simplicial complex. Modern packages for persistent homology often construct Vietoris--Rips or other distance-based simplicial complexes on point clouds because they ... More
Semantic and Influence aware k-Representative Queries over Social StreamsJan 29 2019Massive volumes of data continuously generated on social platforms have become an important information source for users. A primary method to obtain fresh and valuable information from social streams is \emph{social search}. Although there have been extensive ... More
Heterogeneous Network MotifsJan 28 2019Feb 04 2019Many real-world applications give rise to large heterogeneous networks where nodes and edges can be of any arbitrary type (e.g., user, web page, location). Special cases of such heterogeneous graphs include homogeneous graphs, bipartite, k-partite, signed, ... More
Tumor Connectomics: Mapping the intra-tumoral complex interaction networkJan 28 2019Tumors are extremely heterogeneous and comprise of a number of intratumor microenvironments or sub-regions. These tumor microenvironments may interact with eac based on complex high-level relationships, which could provide important insight into the organizational ... More
Log-minor distributions and an application to estimating mean subsystem entropyJan 27 2019A common task in physics, information theory, and other fields is the analysis of properties of subsystems of a given system. Given the covariance matrix $M$ of a system of $n$ coupled variables, the covariance matrices of the subsystems are principal ... More
Computational landscape of user behavior on social mediaJan 25 2019With the increasing abundance of 'digital footprints' left by human interactions in online environments, e.g., social media and app use, the ability to model complex human behavior has become increasingly possible. Many approaches have been proposed, ... More
Optimized Deformed Laplacian for Spectrum-based Community Detection in Sparse Heterogeneous GraphsJan 25 2019Spectral clustering is one of the most popular, yet still incompletely understood, methods for community detection on graphs. In this article we study spectral clustering based on the deformed Laplacian matrix $D-rA$, for sparse heterogeneous graphs (following ... More
Node isolation in large homogeneous binary multiplicative attribute graph modelsJan 24 2019The multiplicative attribute graph (MAG) model was introduced by Kim and Leskovec as a mathematically tractable model of certain classes of real-world networks. It is an instance of hidden graph models, and implements the plausible idea that network structure ... More
Emergence of leader-follower hierarchy among players in an on-line experimentJan 24 2019Hierarchical networks are prevalent in nature and society, corresponding to groups of actors - animals, humans or even robots - organised according to a pyramidal structure with decision makers at the top and followers at the bottom. While this phenomenon ... More
Securing Tag-based recommender systems against profile injection attacks: A comparative study. (Extended Report)Jan 24 2019This work addresses the challenges related to attacks on collaborative tagging systems, which often comes in a form of malicious annotations or profile injection attacks. In particular, we study various countermeasures against two types of such attacks ... More
Reentrant phase transitions in threshold driven contagion on multiplex networksJan 24 2019Models of threshold driven contagion successfully explain the cascading spread of information, behaviour, systematic risks and epidemics on social, financial and biological networks. Contradicting real observations, on single-layer networks with sufficiently ... More
Approximate k-Cover in Hypergraphs: Efficient Algorithms, and ApplicationsJan 23 2019Given a weighted hypergraph $\mathcal{H}(V, \mathcal{E} \subseteq 2^V, w)$, the approximate $k$-cover problem seeks for a size-$k$ subset of $V$ that has the maximum weighted coverage by \emph{sampling only a few hyperedges} in $\mathcal{E}$. The problem ... More
The Junk News Aggregator: Examining junk news posted on Facebook, starting with the 2018 US Midterm ElectionsJan 23 2019Feb 05 2019In recent years, the phenomenon of online misinformation and junk news circulating on social media has come to constitute an important and widespread problem affecting public life online across the globe, particularly around important political events ... More
Navigability evaluation of complex networks by greedy routing efficiencyJan 23 2019Network navigability is a key feature of complex networked systems. For a network embedded in a geometrical space, maximization of greedy routing (GR) measures based on the node geometrical coordinates can ensure efficient greedy navigability. In PNAS, ... More
Mathematical model of gender bias and homophily in professional hierarchiesJan 22 2019Women have become better represented in business, academia, and government over time, yet a dearth of women at the highest levels of leadership remains. Sociologists have attributed the leaky progression of women through professional hierarchies to various ... More
Positioning services of a travel agency in social networksJan 21 2019In this paper the methods of forming a travel company customer base by means of social networks are observed. These methods are made to involve web-users of the social networks (VK.com and Facebook) for positioning of the service of the travel agency ... More
Teaching and learning in uncertaintyJan 21 2019We investigate a simple model for social learning with two agents: a teacher and a student. The teacher's goal is to teach the student the state of the world $\Theta$, however, the teacher herself is not certain about $\Theta$ and needs to simultaneously ... More
Disturbed YouTube for Kids: Characterizing and Detecting Disturbing Content on YouTubeJan 21 2019A considerable number of the most-subscribed YouTube channels feature content popular among children of very young age. Hundreds of toddler-oriented channels on YouTube offer inoffensive, well produced, and educational videos. Unfortunately, inappropriate ... More
Signed Network Structural Analysis and Applications with a Focus on Balance TheoryJan 21 2019We analyse signed networks from the perspective of balance theory which predicts structural balance as a global structure for signed social networks that represent groups of friends and enemies. The scarcity of balanced networks encouraged us to define ... More
A principled methodology for comparing relatedness measures for clustering publicationsJan 21 2019There are many different relatedness measures, based for instance on citation relations or textual similarity, that can be used to cluster scientific publications. We propose a principled methodology for evaluating the accuracy of clustering solutions ... More
Unsupervised User Identity Linkage via Factoid EmbeddingJan 20 2019User identity linkage (UIL), the problem of matching user account across multiple online social networks (OSNs), is widely studied and important to many real-world applications. Most existing UIL solutions adopt a supervised or semi-supervised approach ... More
Cross-referencing Social Media and Public Surveillance Camera Data for Disaster ResponseJan 19 2019Physical media (like surveillance cameras) and social media (like Instagram and Twitter) may both be useful in attaining on-the-ground information during an emergency or disaster situation. However, the intersection and reliability of both surveillance ... More
Characterizing the Use of Images by State-Sponsored Troll Accounts on TwitterJan 17 2019Anecdotal evidence has emerged suggesting that state-sponsored organizations, like the Russian Internet Research Agency, have exploited mainstream social. Their primary goal is apparently to conduct information warfare operations to manipulate public ... More
Differentially-Private Two-Party Egocentric Betweenness CentralityJan 16 2019We describe a novel protocol for computing the egocentric betweenness centrality of a node when relevant edge information is spread between two mutually distrusting parties such as two telecommunications providers. While each node belongs to one network ... More
Learning Vertex Representations for Bipartite NetworksJan 16 2019Recent years have witnessed a widespread increase of interest in network representation learning (NRL). By far most research efforts have focused on NRL for homogeneous networks like social networks where vertices are of the same type, or heterogeneous ... More
Topological Analysis of Bitcoin's Lightning NetworkJan 15 2019Jan 16 2019Bitcoin's Lightning Network (LN) is a scalability solution for Bitcoin allowing transactions to be issued with negligible fees and settled instantly at scale. In order to use LN, funds need to be locked in payment channels on the Bitcoin blockchain (Layer-1) ... More
Spectral rejection for testing hypotheses of structure in networksJan 15 2019Discovering structure in real-world networks requires a suitable null model that defines the absence of meaningful structure. Here we introduce a spectral approach for testing structural hypotheses at both network and node levels, by using generative ... More
BoostNet: Bootstrapping detection of socialbots, and a case study from GuatemalaJan 14 2019We present a method to reconstruct networks of socialbots given minimal input. Then we use Kernel Density Estimates of Botometer scores from 47,000 social networking accounts to find clusters of automated accounts, discovering over 5,000 socialbots. This ... More
Quantifying echo chamber effects in information spreading over political communication networksJan 11 2019Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects ... More
Estimating influenza incidence using search query deceptiveness and generalized ridge regressionJan 11 2019Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current state of the ... More
Network generation and evolution based on spatial and opinion dynamics componentsJan 10 2019In this paper, a model for a spatial network evolution based on a Metropolis simulation is presented. The model uses an energy function that depends both on the distance between the nodes and the stated preferences. The agents influence their network ... More
Review on Graph Feature Learning and Feature Extraction Techniques for Link PredictionJan 10 2019Studying networks to predict the emerging interactions is a common research problem for both fields of network science and machine learning. The problem of predicting future or missing relationships in networks is called link prediction. Machine learning ... More
Fashion and art cycles are driven by counter-dominance signals of elite competition: quantitative evidence from music stylesJan 10 2019Human symbol systems such as art and fashion styles emerge from complex social processes that govern the continuous re-organization of modern societies. They provide a signaling scheme that allows members of an elite to distinguish themselves from the ... More