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Separating Structure from Noise in Large Graphs Using the Regularity LemmaMay 16 2019How can we separate structural information from noise in large graphs? To address this fundamental question, we propose a graph summarization approach based on Szemer\'edi's Regularity Lemma, a well-known result in graph theory, which roughly states that ... More
On the Fairness of Time-Critical Influence Maximization in Social NetworksMay 16 2019Influence maximization has found applications in a wide range of real-world problems, for instance, viral marketing of products in an online social network, and information propagation of valuable information such as job vacancy advertisements and health-related ... More
Control complexity: Diversity of structural controllability of complex networks with given degree sequenceMay 16 2019The necessary number of external signals or driver nodes needed to control a complex network has emerged as an important measure of controllability. Here, we investigate how the degree sequence of directed networks constrains the number of driver nodes. ... More
An interdisciplinary survey of network similarity methodsMay 15 2019Comparative graph and network analysis play an important role in both systems biology and pattern recognition, but existing surveys on the topic have historically ignored or underserved one or the other of these fields. We present an integrative introduction ... More
InfoRest: Restricting Privacy Leakage to Online Social Network AppMay 15 2019In recent years, Online Social Networks (OSNs) have become immensely popular as social interaction services among worldwide Internet users. OSNs facilitate Third-party applications (TPAs) which provide many additional functionalities to users. While providing ... More
GMNN: Graph Markov Neural NetworksMay 15 2019This paper studies semi-supervised object classification in relational data, which is a fundamental problem in relational data modeling. The problem has been extensively studied in the literature of both statistical relational learning (e.g. relational ... More
VICSOM: VIsual Clues from SOcial Media for psychological assessmentMay 15 2019Sharing multimodal information (typically images, videos or text) in Social Network Sites (SNS) occupies a relevant part of our time. The particular way how users expose themselves in SNS can provide useful information to infer human behaviors. This paper ... More
The Mobility Network of Scientists: Analyzing Temporal Correlations in Scientific CareersMay 15 2019To understand the mobility patterns of scientists, we combine two large-scale bibliographic data sets to reveal the geographical "career trajectories" of scientists and their temporal properties. Each trajectory contains, on the individual level, information ... More
User profiles matching for different social networks based on faces embeddingsMay 15 2019It is common practice nowadays to use multiple social networks for different social roles. Although this, these networks assume differences in content type, communications and style of speech. If we intend to understand human behaviour as a key-feature ... More
GhostLink: Latent Network Inference for Influence-aware RecommendationMay 15 2019Social influence plays a vital role in shaping a user's behavior in online communities dealing with items of fine taste like movies, food, and beer. For online recommendation, this implies that users' preferences and ratings are influenced due to other ... More
Planted Hitting Set Recovery in HypergraphsMay 14 2019In various application areas, networked data is collected by measuring interactions involving some specific set of core nodes. This results in a network dataset containing the core nodes along with a potentially much larger set of fringe nodes that all ... More
Stochastic Blockmodels meet Graph Neural NetworksMay 14 2019Stochastic blockmodels (SBM) and their variants, $e.g.$, mixed-membership and overlapping stochastic blockmodels, are latent variable based generative models for graphs. They have proven to be successful for various tasks, such as discovering the community ... More
ActiveHNE: Active Heterogeneous Network EmbeddingMay 14 2019Heterogeneous network embedding (HNE) is a challenging task due to the diverse node types and/or diverse relationships between nodes. Existing HNE methods are typically unsupervised. To maximize the profit of utilizing the rare and valuable supervised ... More
ActiveHNE: Active Heterogeneous Network EmbeddingMay 14 2019May 15 2019Heterogeneous network embedding (HNE) is a challenging task due to the diverse node types and/or diverse relationships between nodes. Existing HNE methods are typically unsupervised. To maximize the profit of utilizing the rare and valuable supervised ... More
LikeStarter: a Smart-contract based Social DAO for CrowdfundingMay 14 2019Crowdfunding has become a popular form of collective funding, in which small donations or investments, made by groups of people, support the development of new projects in exchange of free products or different types of recognition. Social network sites, ... More
Query Processing on Large Graphs: Approaches To Scalability and Response Time Trade OffsMay 14 2019With the advent of social networks and the web, the graph sizes have grown too large to fit in main memory precipitating the need for alternative approaches for an efficient, scalable evaluation of queries on graphs of any size. Here, we use the divide ... More
Consequential Ranking Algorithms and Long-term WelfareMay 13 2019Ranking models are typically designed to provide rankings that optimize some measure of immediate utility to the users. As a result, they have been unable to anticipate an increasing number of undesirable long-term consequences of their proposed rankings, ... More
Friendship Paradox Biases Perceptions in Directed NetworksMay 13 2019How popular a topic or an opinion appears to be in a network can be very different from its actual popularity. For example, in an online network of a social media platform, the number of people who mention a topic in their posts---i.e., its global popularity---can ... More
Transtemporal edges and crosslayer edges in incompressible high-order networksMay 13 2019This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph representation. We study some of their network topological properties and how these may be related to real-world complex ... More
When Do People Trust Their Social Groups?May 13 2019Trust facilitates cooperation and supports positive outcomes in social groups, including member satisfaction, information sharing, and task performance. Extensive prior research has examined individuals' general propensity to trust, as well as the factors ... More
Exogenous Rewards for Promoting Cooperation in Scale-Free NetworksMay 13 2019The design of mechanisms that encourage pro-social behaviours in populations of self-regarding agents is recognised as a major theoretical challenge within several areas of social, life and engineering sciences. When interference from external parties ... More
Physically-interpretable classification of network dynamics for complex collective motionsMay 13 2019Understanding complex network dynamics is a fundamental issue in various scientific and engineering fields. Network theory is capable of revealing the relationship between elements and their propagation; however, for complex collective motions, the network ... More
Emergence of an Onion-like Network in Surface Growth and Its Strong RobustnessMay 13 2019We numerically investigate that optimal robust onion-like networks can emerge even with the constraint of surface growth in supposing a spatially embedded transportation or communication system. To be onion-like, moderately long links are necessary in ... More
The Secret Lives of Names? Name Embeddings from Social MediaMay 12 2019Your name tells a lot about you: your gender, ethnicity and so on. It has been shown that name embeddings are more effective in representing names than traditional substring features. However, our previous name embedding model is trained on private email ... More
Election Control with Voters' Uncertainty: Hardness and Approximation ResultsMay 12 2019The election control problem asks to find a set of nodes in a social network of voters to be the starters of a political campaign aimed at supporting a given target candidate. When a voter is reached by the campaign it changes its opinion on the candidates. ... More
Language in Our Time: An Empirical Analysis of HashtagsMay 11 2019Hashtags in online social networks have gained tremendous popularity during the past five years. The resulting large quantity of data has provided a new lens into modern society. Previously, researchers mainly rely on data collected from Twitter to study ... More
Dissecting Graph Neural Networks on Graph ClassificationMay 11 2019Graph Neural Nets (GNNs) have received increasing attentions, partially due to their superior performance in many node and graph classification tasks. However, there is a lack of understanding on what they are learning and how sophisticated the learned ... More
Mining Hidden Populations through Attributed SearchMay 11 2019Researchers often query online social platforms through their application programming interfaces (API) to find target populations such as people with mental illness~\cite{De-Choudhury2017} and jazz musicians~\cite{heckathorn2001finding}. Entities of such ... More
A class of randomized Subset Selection Methods for large complex networksMay 11 2019Most of the real world complex networks such as the Internet, World Wide Web and collaboration networks are huge; and to infer their structure and dynamics one requires handling large connectivity (adjacency) matrices. Also, to find out the spectra of ... More
Influencing Opinions of Heterogeneous Populations over Finite Time HorizonsMay 11 2019In this work, we focus on strategies to influence the opinion dynamics of a well-connected society. We propose a generalization of the popular voter model. This variant of the voter model can capture a wide range of individuals including strong-willed ... More
Seeding with Costly Network InformationMay 10 2019The spread of behavior over social networks depends on the contact structure among individuals, and seeding the most influential agents can substantially enhance the extent of the spread. While the choice of the best seed set, known as influence maximization, ... More
Check-It: A Plugin for Detecting and Reducing the Spread of Fake News and Misinformation on the WebMay 10 2019Over the past few years, we have been witnessing the rise of misinformation on the Web. People fall victims of fake news during their daily lives and assist their further propagation knowingly and inadvertently. There have been many initiatives that are ... More
On the Inevitability of Online Echo ChambersMay 10 2019While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as "echo chambers." Here we study the conditions ... More
Linear Work Generation of R-MAT GraphsMay 09 2019R-MAT is a simple, widely used recursive model for generating `complex network' graphs with a power law degree distribution and community structure. We make R-MAT even more useful by reducing the required work per edge from logarithmic to constant. The ... More
Detecting Vietnamese Opinion SpamMay 09 2019Recently, Vietnamese Natural Language Processing has been researched by experts in academic and business. However, the existing papers have been focused only on information classification or extraction from documents. Nowadays, with quickly development ... More
Fairness across Network Positions in Cyberbullying Detection AlgorithmsMay 09 2019Cyberbullying, which often has a deeply negative impact on the victim, has grown as a serious issue in Online Social Networks. Recently, researchers have created automated machine learning algorithms to detect Cyberbullying using social and textual features. ... More
Embedding vertex intrinsic relevance in network analysis: the case of BetweennessMay 08 2019Complex network theory (CNT) is an expanding science whose basis are the concepts of graph theory. CNT deals with analyzing networked systems considering vertex exchanging information by means of edges, eventually considering connections strength using ... More
Interdisciplinary Relationships Between Biological and Physical SciencesMay 08 2019Several interdisciplinary areas have appeared at the interface between biological and physical sciences. In this work, we suggest a complex network-based methodology for analyzing the interrelationships between some of these interdisciplinary areas, including ... More
The Art of Social Bots: A Review and a Refined TaxonomyMay 08 2019Social bots represent a new generation of bots that make use of online social networks (OSNs) as a command and control (C\&C) channel. Malicious social bots were responsible for launching large-scale spam campaigns, promoting low-cap stocks, manipulating ... More
A hybrid recommendation algorithm based on weighted stochastic block modelMay 08 2019Hybrid recommendation usually combines collaborative filtering with content-based filtering to exploit merits of both techniques. It is widely accepted that hybrid filtering outperforms the single algorithm, thus it has been the new trend in electronic ... More
Quantifying Triadic Closure in Multi-Edge Social NetworksMay 08 2019Multi-edge networks capture repeated interactions between individuals. In social networks, such edges often form closed triangles, or triads. Standard approaches to measure this triadic closure, however, fail for multi-edge networks, because they do not ... More
Multi-class Twitter Data Categorization and Geocoding with a Novel Computing FrameworkMay 08 2019Transportation data analysis is becoming a major area of computing application. Operation and management of transportation system have been transforming with the advancements in computing technology. This study presents such an advancement in transportation ... More
Displaying Things in Common to Encourage Friendship Formation: A Large Randomized Field ExperimentMay 07 2019Friendship formation is important to online social network sites and to society, but can suffer from informational friction. In this study, we demonstrate that social networks may effectively use an IT-facilitated intervention -- displaying things in ... More
The Alt-Right and Global Information WarfareMay 07 2019The Alt-Right is a neo-fascist white supremacist movement that is involved in violent extremism and shows signs of engagement in extensive disinformation campaigns. Using social media data mining, this study develops a deeper understanding of such targeted ... More
PocketCare: Tracking the Flu with Mobile Phones using Partial Observations of Proximity and SymptomsMay 07 2019Mobile phones provide a powerful sensing platform that researchers may adopt to understand proximity interactions among people and the diffusion, through these interactions, of diseases, behaviors, and opinions. However, it remains a challenge to track ... More
Interactive Search and Exploration in Online Discussion Forums Using Multimodal EmbeddingsMay 07 2019In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analyst to identify and select users of interest, and to find similar users in ... More
On bias in social reviews of university coursesMay 06 2019University course ranking forums are a popular means of disseminating information about satisfaction with the quality of course content and instruction, especially with undergraduate students. A variety of policy decisions by university administrators, ... More
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social ContextsMay 06 2019Recent interest in graph embedding methods has focused on learning a single representation for each node in the graph. But can nodes really be best described by a single vector representation? In this work, we propose a method for learning multiple representations ... More
What do we see when we look at networksMay 06 2019It is an increasingly common practice in several natural and social sciences to rely on network visualisations both as heuristic tools to get a first overview of relational datasets and as a way to offer an illustration of network analysis findings. Such ... More
Understanding Perceptions of Problematic Facebook Use: When People Experience Negative Life Impact and a Lack of ControlMay 06 2019While many people use social network sites to connect with friends and family, some feel that their use is problematic, seriously affecting their sleep, work, or life. Pairing a survey of 20,000 Facebook users measuring perceptions of problematic use ... More
Universality of population recovery patterns after disastersMay 06 2019Despite the rising importance of enhancing community resilience to disasters, our understanding on how communities recover from catastrophic events is limited. Here we study the population recovery dynamics of disaster affected regions by observing the ... More
Same Influenza, Different Responses: Social Media Can Sense a Regional Spectrum of SymptomsMay 06 2019Influenza is an acute respiratory infection caused by a virus. It is highly contagious and rapidly mutative. However, its epidemiological characteristics are conventionally collected in terms of outpatient records. In fact, the subjective bias of the ... More
Internet, Social Media and Conflict Studies Can Greater Interdisciplinarity Solve the Analytical Deadlocks in Cybersecurity Research?May 06 2019In recent years, computational research methods, digital trace data and online human interactions have contributed to the emergence of new technology-oriented sub-fields within International Relations (IR). Although the cybersecurity scholarship had an ... More
Vertex Nomination, Consistent Estimation, and Adversarial ModificationMay 06 2019Given a pair of graphs $G_1$ and $G_2$ and a vertex set of interest in $G_1$, the vertex nomination problem seeks to find the corresponding vertices of interest in $G_2$ (if they exist) and produce a rank list of the vertices in $G_2$, with the corresponding ... More
Vertex Nomination, Consistent Estimation, and Adversarial ModificationMay 06 2019May 15 2019Given a pair of graphs $G_1$ and $G_2$ and a vertex set of interest in $G_1$, the vertex nomination problem seeks to find the corresponding vertices of interest in $G_2$ (if they exist) and produce a rank list of the vertices in $G_2$, with the corresponding ... More
Representation Learning for Attributed Multiplex Heterogeneous NetworkMay 05 2019Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and cannot scale well to handle large networks. Many real-world networks consist ... More
On the Controllability of Clustered Scale-Free NetworksMay 05 2019In this paper, we compare the number of unmatched nodes and the size of dilations in two main random network models, the Scale-Free and Clustered Scale-Free networks. The number of unmatched nodes determines the necessary number of control inputs and ... More
Public vs Media Opinion on RobotsMay 05 2019Fast proliferation of robots in people's everyday lives during recent years calls for a profound examination of public consensus, which is the ultimate determinant of the future of this industry. This paper investigates text corpora, consisting of posts ... More
Detecting Pathogenic Social Media Accounts without Content or Network StructureMay 04 2019The spread of harmful mis-information in social media is a pressing problem. We refer accounts that have the capability of spreading such information to viral proportions as "Pathogenic Social Media" accounts. These accounts include terrorist supporters ... More
An End-to-End Framework to Identify Pathogenic Social Media Accounts on TwitterMay 04 2019Pathogenic Social Media (PSM) accounts such as terrorist supporter accounts and fake news writers have the capability of spreading disinformation to viral proportions. Early detection of PSM accounts is crucial as they are likely to be key users to make ... More
Latent Unexpected and Useful RecommendationMay 04 2019Providing unexpected recommendations is an important task for recommender systems. To do this, we need to start from the expectations of users and deviate from these expectations when recommending items. Previously proposed approaches model user expectations ... More
DynComm R Package -- Dynamic Community Detection for Evolving NetworksMay 04 2019Nowadays, the analysis of dynamics in networks represents a great deal in the Social Network Analysis research area. To support students, teachers, developers, and researchers in this work we introduce a novel R package, namely DynComm. It is designed ... More
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility DataMay 03 2019Urban dispersal events are processes where an unusually large number of people leave the same area in a short period. Early prediction of dispersal events is important in mitigating congestion and safety risks and making better dispatching decisions for ... More
Network interpolationMay 03 2019Given a set of snapshots from a temporal network we develop, analyze, and experimentally validate a so-called network interpolation scheme. Our method allows us to build a plausible sequence of graphs that transition between any two given graphs. Importantly, ... More
Enterprise Cyber Resiliency Against Lateral Movement: A Graph Theoretic ApproachMay 03 2019Lateral movement attacks are a serious threat to enterprise security. In these attacks, an attacker compromises a trusted user account to get a foothold into the enterprise network and uses it to attack other trusted users, increasingly gaining higher ... More
Network Representation Learning: Consolidation and Renewed BearingMay 02 2019Graphs are a natural abstraction for many problems where nodes represent entities and edges represent a relationship across entities. An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear ... More
A Topic-Agnostic Approach for Identifying Fake News PagesMay 02 2019Fake news and misinformation have been increasingly used to manipulate popular opinion and influence political processes. To better understand fake news, how they are propagated, and how to counter their effect, it is necessary to first identify them. ... More
Opinion Diversity and Social Bubbles in Adaptive Sznajd NetworksMay 02 2019Understanding the way in which human opinion changes along time and space constitutes one of the great challenges in complex systems research. Among the several approaches that have been attempted at studying this problem, the Sznajd model provides some ... More
Characterizing Attention Cascades in WhatsApp GroupsMay 02 2019An important political and social phenomena discussed in several countries, like India and Brazil, is the use of WhatsApp to spread false or misleading content. However, little is known about the information dissemination process in WhatsApp groups. Attention ... More
Characterizing Attention Cascades in WhatsApp GroupsMay 02 2019May 04 2019An important political and social phenomena discussed in several countries, like India and Brazil, is the use of WhatsApp to spread false or misleading content. However, little is known about the information dissemination process in WhatsApp groups. Attention ... More
Temporal Ordered Clustering in Dynamic NetworksMay 02 2019In temporal ordered clustering, given a single snapshot of a dynamic network, we aim at partitioning its nodes into $K$ ordered clusters $C_1 \prec \cdots \prec C_K$ such that for $i<j$ nodes in cluster $C_i$ arrive to the dynamic graph before nodes in ... More
Temporal Ordered Clustering in Dynamic NetworksMay 02 2019May 07 2019In temporal ordered clustering, given a single snapshot of a dynamic network, we aim at partitioning its nodes into $K$ ordered clusters $C_1 \prec \cdots \prec C_K$ such that for $i<j$ nodes in cluster $C_i$ arrive to the dynamic graph before nodes in ... More
On two existing approaches to statistical analysis of social media dataMay 02 2019Using social media data for statistical analysis of general population faces commonly two basic obstacles: firstly, social media data are collected for different objects than the population units of interest; secondly, the relevant measures are typically ... More
Reliability of relational event model estimates under sampling: how to fit a relational event model to 360 million dyadic eventsMay 02 2019We assess the reliability of relational event model parameters estimated under two sampling schemes: (1) uniform sampling from the observed events and (2) case-control sampling which samples non-events, or null dyads ("controls"), from a suitably defined ... More
Nonlocal transformations of the Generalized Liénard type equations and dissipative Ermakov-Milne-Pinney systemsMay 02 2019We employ the method of nonlocal generalized Sundman transformations to formulate the linearization problem for equations of the generalized Li\'enard type and show that they may be mapped to equations of the dissipative Ermakov-Milne-Pinney type. We ... More
Reputation-Based Information Design for Inducing Prosocial BehaviorMay 02 2019We study the idea of information design for inducing prosocial behavior in the context of electricity consumption. We consider a continuum of agents. Each agent has a different intrinsic motivation to reduce her power consumption. Each agent models the ... More
Social Network of Extreme Tweeters: A Case StudyMay 02 2019The number of posts made by a single user account on a social media platform Twitter in any given time interval is usually quite low. However, there is a subset of users whose volume of posts is much higher than the median. In this paper, we investigate ... More
Drug-Drug Adverse Effect Prediction with Graph Co-AttentionMay 02 2019Complex or co-existing diseases are commonly treated using drug combinations, which can lead to higher risk of adverse side effects. The detection of polypharmacy side effects is usually done in Phase IV clinical trials, but there are still plenty which ... More
Multi-component generalizations of mKdV equation and non-associative algebraic structuresMay 01 2019Relations between triple Jordan systems and integrable multi-component models of the modified Korteveg--de Vries type are established. The most general model is related to a pair consisting of a triple Jordan system and a skew-symmetric bilinear operation. ... More
Applications of Social Media in Hydroinformatics: A SurveyMay 01 2019Floods of research and practical applications employ social media data for a wide range of public applications, including environmental monitoring, water resource managing, disaster and emergency response.Hydroinformatics can benefit from the social media ... More
Clustering-Based Collaborative Filtering Using an Incentivized/Penalized User ModelMay 01 2019Giving or recommending appropriate content based on the quality of experience is the most important and challenging issue in recommender systems. As collaborative filtering (CF) is one of the most prominent and popular techniques used for recommender ... More
On the Use of ArXiv as a DatasetApr 30 2019The arXiv has collected 1.5 million pre-print articles over 28 years, hosting literature from scientific fields including Physics, Mathematics, and Computer Science. Each pre-print features text, figures, authors, citations, categories, and other metadata. ... More
MixHop: Higher-Order Graph Convolution Architectures via Sparsified Neighborhood MixingApr 30 2019Existing popular methods for semi-supervised learning with Graph Neural Networks (such as the Graph Convolutional Network) provably cannot learn a general class of neighborhood mixing relationships. To address this weakness, we propose a new model, MixHop, ... More
A Scale-Consistent Approach for Recommender SystemsApr 30 2019In 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 ... More
The Role of User Profile for Fake News DetectionApr 30 2019Consuming news from social media is becoming increasingly popular. Social media appeals to users due to its fast dissemination of information, low cost, and easy access. However, social media also enables the widespread of fake news. Because of the detrimental ... More
Computational Models for Commercial Advertisements in Social NetworksApr 30 2019Identifying noteworthy spreaders in a network is essential for understanding the spreading process and controlling the reach of the spread in the network. The nodes that are holding more intrinsic power to extend the reach of the spread are important ... More
The Guided Team-Partitioning Problem: Definition, Complexity, and AlgorithmApr 30 2019A long line of literature has focused on the problem of selecting a team of individuals from a large pool of candidates, such that certain constraints are respected, and a given objective function is maximized. Even though extant research has successfully ... More
Online reviews can predict long-term returns of individual stocksApr 30 2019Online reviews are feedback voluntarily posted by consumers about their consumption experiences. This feedback indicates customer attitudes such as affection, awareness and faith towards a brand or a firm and demonstrates inherent connections with a company's ... More
Triangle Preferential Attachment Has Power-law Degrees and Eigenvalues; Eigenvalues Are More Stable to Network SamplingApr 29 2019Preferential attachment models are a common class of graph models which have been used to explain why power-law distributions appear in the degree sequences of real network data. One of the things they lack, however, is higher-order network clustering, ... More
Local non-Bayesian social learning with stubborn agentsApr 29 2019In recent years, people have increasingly turned to social networks like Twitter and Facebook for news. In contrast to traditional news sources, these platforms allow users to simultaneously read news articles and share opinions with other users. Among ... More
A Deep Generative Model for Graph LayoutApr 27 2019As different layouts can characterize different aspects of the same graph, finding a "good" layout of a graph is an important task for graph visualization. In practice, users often visualize a graph in multiple layouts by using different methods and varying ... More
High Quality Degree Based Heuristics for the Influence Maximization ProblemApr 27 2019The problem of influence maximization is to select the most influential individuals in a social network. With the popularity of social network sites, and the development of viral marketing, the importance of the problem has been increased. The influence ... More
A Socio-Informatic Approach to Automated Account Classification on Social MediaApr 27 2019Automated accounts on social media have become increasingly problematic. We propose a key feature in combination with existing methods to improve machine learning algorithms for bot detection. We successfully improve classification performance through ... More
Exploring Information Centrality for Intrusion Detection in Large NetworksApr 27 2019Modern networked systems are constantly under threat from systemic attacks. There has been a massive upsurge in the number of devices connected to a network as well as the associated traffic volume. This has intensified the need to better understand all ... More
StartupBR: Higher Education's Influence on Social Networks and Entrepreneurship in BrazilApr 26 2019Developing and middle-income countries increasingly empha-size higher education and entrepreneurship in their long-term develop-ment strategy. Our work focuses on the influence of higher education institutions (HEIs) on startup ecosystems in Brazil, an ... More
StartupBR: Higher Education's Influence on Social Networks and Entrepreneurship in BrazilApr 26 2019Apr 30 2019Developing and middle-income countries increasingly empha-size higher education and entrepreneurship in their long-term develop-ment strategy. Our work focuses on the influence of higher education institutions (HEIs) on startup ecosystems in Brazil, an ... More
Spectral partitioning of time-varying networks with unobserved edgesApr 26 2019We discuss a variant of `blind' community detection, in which we aim to partition an unobserved network from the observation of a (dynamical) graph signal defined on the network. We consider a scenario where our observed graph signals are obtained by ... More
Preferential attachment without vertex growth: emergence of the giant componentApr 26 2019We study the following preferential attachment variant of the classical Erdos-Renyi random graph process. Starting with an empty graph on n vertices, new edges are added one-by-one, and each time an edge is chosen with probability roughly proportional ... More
Neural Ideal Point Estimation NetworkApr 26 2019Understanding politics is challenging because the politics take the influence from everything. Even we limit ourselves to the political context in the legislative processes; we need a better understanding of latent factors, such as legislators, bills, ... More
Hierarchical Context enabled Recurrent Neural Network for RecommendationApr 26 2019A long user history inevitably reflects the transitions of personal interests over time. The analyses on the user history require the robust sequential model to anticipate the transitions and the decays of user interests. The user history is often modeled ... More