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  • Human biases in body measurement estimation
    arXiv.cs.SI Pub Date : 2020-09-16
    Kirill Martynov; Kiran Garimella; Robert West

    Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it is currently not well understood how accurately humans can assess weight and height from images, and when and how they fail. To bridge this gap,

    更新日期:2020-09-18
  • Characterizing Attitudinal Network Graphs through Frustration Cloud
    arXiv.cs.SI Pub Date : 2020-09-16
    Lucas Rusnak; Jelena Tešić

    Attitudinal Network Graphs (ANG) are network graphs where edges capture an expressed opinion: two vertices connected by an edge can be agreeable (positive) or antagonistic (negative). Measure of consensus in attitudinal graph reflects how easy or difficult consensus can be reached that is acceptable by everyone. Frustration index is one such measure as it determines the distance of a network from a

    更新日期:2020-09-18
  • Adoption of Twitter's New Length Limit: Is 280 the New 140?
    arXiv.cs.SI Pub Date : 2020-09-16
    Kristina Gligorić; Ashton Anderson; Robert West

    In November 2017, Twitter doubled the maximum allowed tweet length from 140 to 280 characters, a drastic switch on one of the world's most influential social media platforms. In the first long-term study of how the new length limit was adopted by Twitter users, we ask: Does the effect of the new length limit resemble that of the old one? Or did the doubling of the limit fundamentally change how Twitter

    更新日期:2020-09-18
  • Scikit-network: Graph Analysis in Python
    arXiv.cs.SI Pub Date : 2020-09-14
    Thomas BonaldIP Paris; Nathan de LaraIP Paris; Quentin LutzIP Paris; Bertrand CharpentierTUM

    Scikit-network is a Python package inspired by scikit-learn for the analysis of large graphs. Graphs are represented by their adjacency matrix in the sparse CSR format of SciPy. The package provides state-of-the-art algorithms for ranking, clustering, classifying, embedding and visualizing the nodes of a graph. High performance is achieved through a mix of fast matrix-vector products (using SciPy)

    更新日期:2020-09-18
  • Detectability of hierarchical communities in networks
    arXiv.cs.SI Pub Date : 2020-09-16
    Leto Peel; Michael T. Schaub

    We study the problem of recovering a planted hierarchy of partitions in a network. The detectability of a single planted partition has previously been analysed in detail and a phase transition has been identified below which the partition cannot be detected. Here we show that, in the hierarchical setting, there exist additional phases in which the presence of multiple consistent partitions can either

    更新日期:2020-09-18
  • Helping Users Tackle Algorithmic Threats on Social Media: A Multimedia Research Agenda
    arXiv.cs.SI Pub Date : 2020-08-26
    Christian von der Weth; Ashraf Abdul; Shaojing Fan; Mohan Kankanhalli

    Participation on social media platforms has many benefits but also poses substantial threats. Users often face an unintended loss of privacy, are bombarded with mis-/disinformation, or are trapped in filter bubbles due to over-personalized content. These threats are further exacerbated by the rise of hidden AI-driven algorithms working behind the scenes to shape users' thoughts, attitudes, and behavior

    更新日期:2020-09-18
  • Exploring Speech Cues in Web-mined COVID-19 Conversational Vlogs
    arXiv.cs.SI Pub Date : 2020-09-16
    Kexin Feng; Preeti Zanwar; Amir H. Behzadan; Theodora Chaspari

    The COVID-19 pandemic caused by the novel SARS-Coronavirus-2 (n-SARS-CoV-2) has impacted people's lives in unprecedented ways. During the time of the pandemic, social vloggers have used social media to actively share their opinions or experiences in quarantine. This paper collected videos from YouTube to track emotional responses in conversational vlogs and their potential associations with events

    更新日期:2020-09-18
  • Semantic Property Graph for Scalable Knowledge Graph Analytics
    arXiv.cs.SI Pub Date : 2020-09-16
    Sumit Purohit; Nhuy Van

    Graphs are a natural and fundamental representation of describing the activities, relationships, and evolution of various complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data

    更新日期:2020-09-18
  • Does Link Prediction Help Detect Feature Interactions in Software Product Lines (SPLs)?
    arXiv.cs.SI Pub Date : 2020-09-15
    Seyedehzahra Khoshmanesh; Robyn Lutz

    An ongoing challenge for the requirements engineering of software product lines is to predict whether a new combination of features (units of functionality) will create an unwanted or even hazardous feature interaction. We thus seek to improve and automate the prediction of unwanted feature interactions early in development. In this paper, we show how the detection of unwanted feature interactions

    更新日期:2020-09-18
  • Sustained Online Amplification of COVID-19 Elites in the United States
    arXiv.cs.SI Pub Date : 2020-09-15
    Ryan J. Gallagher; Larissa Doroshenko; Sarah Shugars; David Lazer; Brooke Foucault Welles

    The ongoing, fluid nature of the COVID-19 pandemic requires individuals to regularly seek information about best health practices, local community spreading, and public health guidelines. In the absence of a unified response to the pandemic in the United States and clear, consistent directives from federal and local officials, people have used social media to collectively crowdsource COVID-19 elites

    更新日期:2020-09-16
  • Auditing the Sensitivity of Graph-based Ranking with Visual Analytics
    arXiv.cs.SI Pub Date : 2020-09-15
    Tiankai Xie; Yuxin Ma; Hanghang Tong; My T. Thai; Ross Maciejewski

    Graph mining plays a pivotal role across a number of disciplines, and a variety of algorithms have been developed to answer who/what type questions. For example, what items shall we recommend to a given user on an e-commerce platform? The answers to such questions are typically returned in the form of a ranked list, and graph-based ranking methods are widely used in industrial information retrieval

    更新日期:2020-09-16
  • Hierarchical community structure in networks
    arXiv.cs.SI Pub Date : 2020-09-15
    Michael T. Schaub; Leto Peel

    Modular and hierarchical structures are pervasive in real-world complex systems. A great deal of effort has gone into trying to detect and study these structures. Important theoretical advances in the detection of modular, or "community", structures have included identifying fundamental limits of detectability by formally defining community structure using probabilistic generative models. Detecting

    更新日期:2020-09-16
  • The impact of supply-chain networks on interactions between the anti-COVID-19 lockdowns in different regions
    arXiv.cs.SI Pub Date : 2020-09-15
    Hiroyasu Inoue; Yohsuke Murase; Yasuyuki Todo

    To prevent the spread of COVID-19, many cities, states, and countries have `locked down', restricting economic activities in non-essential sectors. Such lockdowns have substantially shrunk production in most countries. This study examines how the economic effects of lockdowns in different regions interact through supply chains, a network of firms for production, simulating an agent-based model of production

    更新日期:2020-09-16
  • Understanding Global Reaction to the Recent Outbreaks of COVID-19: Insights from Instagram Data Analysis
    arXiv.cs.SI Pub Date : 2020-09-15
    Abdul Muntakim Rafi; Shivang Rana; Rajwinder Kaur; Q. M. Jonathan Wu; Pooya Moradian Zadeh

    The coronavirus disease, also known as the COVID-19, is an ongoing pandemic of a severe acute respiratory syndrome. The pandemic has led to the cancellation of many religious, political, and cultural events around the world. A huge number of people have been stuck within their homes because of unprecedented lockdown measures taken globally. This paper examines the reaction of individuals to the virus

    更新日期:2020-09-16
  • Joint Subgraph-to-Subgraph Transitions -- Generalizing Triadic Closure for Powerful and Interpretable Graph Modeling
    arXiv.cs.SI Pub Date : 2020-09-14
    Justus Hibshman; Daniel Gonzalez; Satyaki Sikdar; Tim Weninger

    We generalize triadic closure, along with previous generalizations of triadic closure, under an intuitive umbrella generalization: the Subgraph-to-Subgraph Transition (SST). We present algorithms and code to model graph evolution in terms of collections of these SSTs. We then use the SST framework to create link prediction models for both static and temporal, directed and undirected graphs which produce

    更新日期:2020-09-16
  • Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion
    arXiv.cs.SI Pub Date : 2020-09-15
    Joshua Becker; Abdullah Almaatouq; Agnes Horvat

    Research on belief formation has produced contradictory findings on whether and when communication between group members will improve the accuracy of numeric estimates such as economic forecasts, medical diagnoses, and job candidate assessments. While some evidence suggests that carefully mediated processes such as the "Delphi method" produce more accurate beliefs than unstructured discussion, others

    更新日期:2020-09-16
  • Hierarchical Coarse-grained Approach to the Duration-dependent Spreading Dynamics in Complex Networks
    arXiv.cs.SI Pub Date : 2020-09-15
    Jin-Fu Chen; Yi-Mu Du; Hui Dong; Chang-Pu Sun

    Various coarse-grained models have been proposed to study the spreading dynamics in the network. A microscopic theory is needed to connect the spreading dynamics with the individual behaviors. In this letter, we unify the description of different spreading dynamics on complex networks by decomposing the microscopic dynamics into two basic processes, the aging process and the contact process. A microscopic

    更新日期:2020-09-16
  • On the use of local structural properties for improving the efficiency of hierarchical community detection methods
    arXiv.cs.SI Pub Date : 2020-09-15
    Julio-Omar Palacio-Niño; Fernando Berzal

    Community detection is a fundamental problem in the analysis of complex networks. It is the analogue of clustering in network data mining. Within community detection methods, hierarchical algorithms are popular. However, their iterative nature and the need to recompute the structural properties used to split the network (i.e. edge betweenness in Girvan and Newman's algorithm), make them unsuitable

    更新日期:2020-09-16
  • Discovering Interesting Subgraphs in Social Media Networks
    arXiv.cs.SI Pub Date : 2020-09-12
    Subhasis Dasgupta; Amarnath Gupta

    Social media data are often modeled as heterogeneous graphs with multiple types of nodes and edges. We present a discovery algorithm that first chooses a "background" graph based on a user's analytical interest and then automatically discovers subgraphs that are structurally and content-wise distinctly different from the background graph. The technique combines the notion of a \texttt{group-by} operation

    更新日期:2020-09-15
  • Bluetooth based Proximity, Multi-hop Analysis and Bi-directional Trust: Epidemics and More
    arXiv.cs.SI Pub Date : 2020-09-10
    Ramesh Raskar; Sai Sri Sathya

    In this paper, we propose a trust layer on top of Bluetooth and similar wireless communication technologies that can form mesh networks. This layer as a protocol enables computing trust scores based on proximity and bi-directional transfer of messages in multiple hops across a network of mobile devices. We describe factors and an approach for determining these trust scores and highlight its applications

    更新日期:2020-09-15
  • Sparsity of weighted networks: measures and applications
    arXiv.cs.SI Pub Date : 2020-09-14
    Swati Goswami; Asit K. Das; Subhas C. Nandy

    A majority of real life networks are weighted and sparse. The present article aims at characterization of weighted networks based on sparsity, as a measure of inherent diversity, of different network parameters. It utilizes sparsity index defined on ordered degree sequence of simple networks and derives further properties of this index. The range of possible values of sparsity index of any connected

    更新日期:2020-09-15
  • COMONet: Community Mobile Network
    arXiv.cs.SI Pub Date : 2020-09-13
    Primal Wijesekera; Chamath I. Keppitiyagama

    The density of mobile phones has increased rapidly in recent years. One drawback of the current mobile telephone technology is that it forces all the calls to go through cellular base stations even if the caller and the callee are within the radio range of each other. Hybrid cellular networks and Unlicensed Mobile Access (UMA) have been proposed as solutions that enable mobile phone users to bypass

    更新日期:2020-09-15
  • EdinburghNLP at WNUT-2020 Task 2: Leveraging Transformers with Generalized Augmentation for Identifying Informativeness in COVID-19 Tweets
    arXiv.cs.SI Pub Date : 2020-09-06
    Nickil Maveli

    Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they're observing in real-time. Because of this, more agencies are interested in programatically monitoring Twitter (disaster relief organizations and news agencies) and therefore recognizing the informativeness of a tweet can help filter noise from

    更新日期:2020-09-15
  • An Algorithmic Information Distortion in Multidimensional Networks
    arXiv.cs.SI Pub Date : 2020-09-12
    Felipe S. Abrahão; Klaus Wehmuth; Hector Zenil; Artur Ziviani

    Network complexity, network information content analysis, and lossless compressibility of graph representations have been played an important role in network analysis and network modeling. As multidimensional networks, such as time-varying, multilayer, or dynamic multilayer networks, gain more relevancy in network science, it becomes crucial to investigate in which situations universal algorithmic

    更新日期:2020-09-15
  • Country Image in COVID-19 Pandemic: A Case Study of China
    arXiv.cs.SI Pub Date : 2020-09-12
    Huimin Chen; Zeyu Zhu; Fanchao Qi; Yining Ye; Zhiyuan Liu; Maosong Sun; Jianbin Jin

    Country image has a profound influence on international relations and economic development. In the worldwide outbreak of COVID-19, countries and their people display different reactions, resulting in diverse perceived images among foreign public. Therefore, in this study, we take China as a specific and typical case and investigate its image with aspect-based sentiment analysis on a large-scale Twitter

    更新日期:2020-09-15
  • Characterizing Twitter Interaction during COVID-19 pandemic using Complex Networks and Text Mining
    arXiv.cs.SI Pub Date : 2020-09-11
    Josimar E. Chire-Saire

    The outbreak of covid-19 started many months ago, the reported origin was in Wuhan Market, China. Fastly, this virus was propagated to other countries because the access to international travels is affordable and many countries have a distance of some flight hours, besides borders were a constant flow of people. By the other hand, Internet users have the habits of sharing content using Social Networks

    更新日期:2020-09-15
  • A deep-learning model for evaluating and predicting the impact of lockdown policies on COVID-19 cases
    arXiv.cs.SI Pub Date : 2020-09-11
    Ahmed Ben Said; Abdelkarim Erradi; Hussein Aly; Abdelmonem Mohamed

    To reduce the impact of COVID-19 pandemic most countries have implemented several counter-measures to control the virus spread including school and border closing, shutting down public transport and workplace and restrictions on gathering. In this research work, we propose a deep-learning prediction model for evaluating and predicting the impact of various lockdown policies on daily COVID-19 cases

    更新日期:2020-09-14
  • Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
    arXiv.cs.SI Pub Date : 2020-09-11
    Aravind Sankar; Junting Wang; Adit Krishnan; Hari Sundaram

    We present InfoMotif, a new semi-supervised, motif-regularized, learning framework over graphs. We overcome two key limitations of message passing in popular graph neural networks (GNNs): localization (a k-layer GNN cannot utilize features outside the k-hop neighborhood of the labeled training nodes) and over-smoothed (structurally indistinguishable) representations. We propose the concept of attributed

    更新日期:2020-09-14
  • Sequential seeding in multilayer networks
    arXiv.cs.SI Pub Date : 2020-09-10
    Piotr Bródka; Jarosław Jankowski; Radosław Michalski

    Complex networks are the underlying structures of multiple real-world systems: social, biological, computer, or communication, to name only a few. In many cases, they are helpful in modelling processes that happen on top of them, which leads to gaining more knowledge about these phenomena. One example of such a process is the spread of influence. Here, the members of a social system spread the influence

    更新日期:2020-09-14
  • CasGCN: Predicting future cascade growth based on information diffusion graph
    arXiv.cs.SI Pub Date : 2020-09-10
    Zhixuan Xu; Minghui Qian; Xiaowei Huang; Jie Meng

    Sudden bursts of information cascades can lead to unexpected consequences such as extreme opinions, changes in fashion trends, and uncontrollable spread of rumors. It has become an important problem on how to effectively predict a cascade' size in the future, especially for large-scale cascades on social media platforms such as Twitter and Weibo. However, existing methods are insufficient in dealing

    更新日期:2020-09-14
  • Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse
    arXiv.cs.SI Pub Date : 2020-09-11
    Ancil Crayton; João Fonseca; Kanav Mehra; Michelle Ng; Jared Ross; Marcelo Sandoval-Castañeda; Rachel von Gnechten

    People often turn to social media to comment upon and share information about major global events. Accordingly, social media is receiving increasing attention as a rich data source for understanding people's social, political and economic experiences of extreme weather events. In this paper, we contribute two novel methodologies that leverage Twitter discourse to characterize narratives and identify

    更新日期:2020-09-14
  • WOLI at SemEval-2020 Task 12: Arabic Offensive Language Identification on Different Twitter Datasets
    arXiv.cs.SI Pub Date : 2020-09-11
    Yasser OtiefyWideBot; Ahmed AbdelmalekWideBot; Islam El HosaryWideBot

    Communicating through social platforms has become one of the principal means of personal communications and interactions. Unfortunately, healthy communication is often interfered by offensive language that can have damaging effects on the users. A key to fight offensive language on social media is the existence of an automatic offensive language detection system. This paper presents the results and

    更新日期:2020-09-14
  • Community detection in networks using graph embeddings
    arXiv.cs.SI Pub Date : 2020-09-11
    Aditya Tandon; Aiiad Albeshri; Vijey Thayananthan; Wadee Alhalabi; Filippo Radicchi; Santo Fortunato

    Graph embedding methods are becoming increasingly popular in the machine learning community, where they are widely used for tasks such as node classification and link prediction. Embedding graphs in geometric spaces should aid the identification of network communities as well, because nodes in the same community should be projected close to each other in the geometric space, where they can be detected

    更新日期:2020-09-14
  • Understanding Coarsening for Embedding Large-Scale Graphs
    arXiv.cs.SI Pub Date : 2020-09-10
    Taha Atahan Akyildiz; Amro Alabsi Aljundi; Kamer Kaya

    A significant portion of the data today, e.g, social networks, web connections, etc., can be modeled by graphs. A proper analysis of graphs with Machine Learning (ML) algorithms has the potential to yield far-reaching insights into many areas of research and industry. However, the irregular structure of graph data constitutes an obstacle for running ML tasks on graphs such as link prediction, node

    更新日期:2020-09-11
  • Multi-instance Domain Adaptation for Vaccine Adverse Event Detection
    arXiv.cs.SI Pub Date : 2020-09-09
    Junxiang Wang; Liang Zhao

    Detection of vaccine adverse events is crucial to the discovery and improvement of problematic vaccines. To achieve it, traditionally formal reporting systems like VAERS support accurate but delayed surveillance, while recently social media have been mined for timely but noisy observations. Utilizing the complementary strengths of these two domains to boost the detection performance looks good but

    更新日期:2020-09-11
  • Presentation a Trust Walker for rating prediction in Recommender System with Biased Random Walk: Effects of H-index Centrality, Similarity in Items and Friends
    arXiv.cs.SI Pub Date : 2020-09-10
    Saman Forouzandeh; Mehrdad Rostami; Kamal Berahmand

    The use of recommender systems has increased dramatically to assist online social network users in the decision-making process and selecting appropriate items. On the other hand, due to many different items, users cannot score a wide range of them, and usually, there is a scattering problem for the matrix created for users. To solve the problem, the trust-based recommender systems are applied to predict

    更新日期:2020-09-11
  • Effective Influence Spreading in Temporal Networks with Sequential Seeding
    arXiv.cs.SI Pub Date : 2020-09-10
    Radosław Michalski; Jarosław Jankowski; Piotr Bródka

    The spread of influence in networks is a topic of great importance in many application areas. For instance, one would like to maximise the coverage, limiting the budget for marketing campaign initialisation and use the potential of social influence. To tackle this and similar challenges, more than a decade ago, researchers started to investigate the influence maximisation problem. The challenge is

    更新日期:2020-09-11
  • Optimisation of the coalescent hyperbolic embedding of complex networks
    arXiv.cs.SI Pub Date : 2020-09-10
    Bianka Kovács; Gergely Palla

    Several observations indicate the existence of a latent hyperbolic space behind real networks that makes their structure very intuitive in the sense that the probability for a connection is decreasing with the hyperbolic distance between the nodes. A remarkable network model generating random graphs along this line is the popularity-similarity optimisation (PSO) model, offering a scale-free degree

    更新日期:2020-09-11
  • How Political is the Spread of COVID-19 in the United States? An Analysis using Transportation and Weather Data
    arXiv.cs.SI Pub Date : 2020-09-10
    Karan Vombatkere; Hanjia Lyu; Jiebo Luo

    We investigate the difference in the spread of COVID-19 between the states won by Donald Trump (Red) and the states won by Hillary Clinton (Blue) in the 2016 presidential election, by mining transportation patterns of US residents from March 2020 to July 2020. To ensure a fair comparison, we first use a K-means clustering method to group the 50 states into five clusters according to their population

    更新日期:2020-09-11
  • Institutional Similarity Drives Cultural Similarity among Online Communities
    arXiv.cs.SI Pub Date : 2020-09-09
    Qiankun Zhong; Seth Frey

    Understanding online communities requires an appreciation of both structure and culture. But basic questions remain difficult to pose. How do these facets interact and drive each other? Using data on the membership and governance styles of 5,000 small-scale online communities, we construct empirical measures for cross-server similarities in institutional structure and culture to explore the influence

    更新日期:2020-09-11
  • What Makes People Join Conspiracy Communities?: Role of Social Factors in Conspiracy Engagement
    arXiv.cs.SI Pub Date : 2020-09-09
    Shruti Phadke; Mattia Samory; Tanushree Mitra

    Widespread conspiracy theories, like those motivating anti-vaccination attitudes or climate change denial, propel collective action and bear society-wide consequences. Yet, empirical research has largely studied conspiracy theory adoption as an individual pursuit, rather than as a socially mediated process. What makes users join communities endorsing and spreading conspiracy theories? We leverage longitudinal

    更新日期:2020-09-11
  • Forecasting financial markets with semantic network analysis in the COVID-19 crisis
    arXiv.cs.SI Pub Date : 2020-09-09
    A. Fronzetti Colladon; S. Grassi; F. Ravazzolo; F. Violante

    This paper uses a new textual data index for predicting stock market data. The index is applied to a large set of news to evaluate the importance of one or more general economic related keywords appearing in the text. The index assesses the importance of the economic related keywords, based on their frequency of use and semantic network position. We apply it to the Italian press and construct indices

    更新日期:2020-09-11
  • The 2020 Sturgis Motorcycle Rally and COVID-19
    arXiv.cs.SI Pub Date : 2020-09-05
    Yong Cai; Grant Goehring

    The Sturgis Motorcycle Rally that took place from August 7-16 was one of the largest public gatherings since the start of the COVID-19 outbreak. Over 460,000 visitors from across the United States travelled to Sturgis, South Dakota to attend the ten day event. Using anonymous cell phone tracking data we identify the home counties of visitors to the rally and examine the impact of the rally on the spread

    更新日期:2020-09-11
  • GoCoronaGo: Privacy Respecting Contact Tracing for COVID-19 Management
    arXiv.cs.SI Pub Date : 2020-09-10
    Yogesh Simmhan; Tarun Rambha; Aakash Khochare; Shriram Ramesh; Animesh Baranawal; John Varghese George; Rahul Atul Bhope; Amrita Namtirtha; Amritha Sundararajan; Sharath Suresh Bhargav; Nihar Thakkar; Raj Kiran

    The COVID-19 pandemic is imposing enormous global challenges in managing the spread of the virus. A key pillar to mitigation is contact tracing, which complements testing and isolation. Digital apps for contact tracing using Bluetooth technology available in smartphones have gained prevalence globally. In this article, we discuss various capabilities of such digital contact tracing, and its implication

    更新日期:2020-09-11
  • Nondiagonal Mixture of Dirichlet Network Distributions for Analyzing a Stock Ownership Network
    arXiv.cs.SI Pub Date : 2020-09-08
    Wenning Zhang; Ryohei Hisano; Takaaki Ohnishi; Takayuki Mizuno

    Block modeling is widely used in studies on complex networks. The cornerstone model is the stochastic block model (SBM), widely used over the past decades. However, the SBM is limited in analyzing complex networks as the model is, in essence, a random graph model that cannot reproduce the basic properties of many complex networks, such as sparsity and heavy-tailed degree distribution. In this paper

    更新日期:2020-09-10
  • Beyond Observed Connections : Link Injection
    arXiv.cs.SI Pub Date : 2020-09-02
    Jie Bu; M. Maruf; Arka Daw

    In this paper, we proposed the \textit{link injection}, a novel method that helps any differentiable graph machine learning models to go beyond observed connections from the input data in an end-to-end learning fashion. It finds out (weak) connections in favor of the current task that is not present in the input data via a parametric link injection layer. We evaluate our method on both node classification

    更新日期:2020-09-10
  • A General Model of Opinion Dynamics with Tunable Sensitivity
    arXiv.cs.SI Pub Date : 2020-09-09
    Anastasia Bizyaeva; Alessio Franci; Naomi Ehrich Leonard

    We introduce a general model of continuous-time opinion dynamics for an arbitrary number of agents that communicate over a network and form real-valued opinions about an arbitrary number of options. Drawing inspiration from models in biology, physics, and social psychology, we apply a sigmoidal saturating function to inter-agent and intra-agent exchanges of opinions. The saturating function is the

    更新日期:2020-09-10
  • Social Analytics of Team Interaction using Dynamic Complexity Heat Maps and Network Visualizations
    arXiv.cs.SI Pub Date : 2020-09-07
    Travis J. Wiltshire; Dan Hudson; Philia Lijdsman; Stijn Wever; Martin Atzmueller

    Given the increasing complexity of many sociotechnical work domains, effective teamwork is becoming more and more crucial. While face-to-face communication contributes to effective teamwork, understanding the time-varying nature and structure of team communication is limited. In this work, we combine sensor-based social analytics of Socio-metric badges (Rhythm Badge) with two visualization techniques

    更新日期:2020-09-10
  • Quantifying the Effects of COVID-19 on Mental Health Support Forums
    arXiv.cs.SI Pub Date : 2020-09-08
    Laura Biester; Katie Matton; Janarthanan Rajendran; Emily Mower Provost; Rada Mihalcea

    The COVID-19 pandemic, like many of the disease outbreaks that have preceded it, is likely to have a profound effect on mental health. Understanding its impact can inform strategies for mitigating negative consequences. In this work, we seek to better understand the effects of COVID-19 on mental health by examining discussions within mental health support communities on Reddit. First, we quantify the

    更新日期:2020-09-10
  • QSAN: A Quantum-probability based Signed Attention Network for Explainable False Information Detection
    arXiv.cs.SI Pub Date : 2020-09-08
    Tian Tian; Yudong Liu; Xiaoyu Yang; Yuefei Lyu; Xi Zhang; Binxing Fang

    False information detection on social media is challenging as it commonly requires tedious evidence-collecting but lacks available comparative information. Clues mined from user comments, as the wisdom of crowds, could be of considerable benefit to this task. However, it is non-trivial to capture the complex semantics from the contents and comments in consideration of their implicit correlations. Although

    更新日期:2020-09-10
  • A Longitudinal Analysis of a Social Network of Intellectual History
    arXiv.cs.SI Pub Date : 2020-09-08
    Cindarella Petz; Raji Ghawi; Jürgen Pfeffer

    The history of intellectuals consists of a complicated web of influences and interconnections of philosophers, scientists, writers, their work, and ideas. How did these influences evolve over time? Who were the most influential scholars in a period? To answer these questions, we mined a network of influence of over 12,500 intellectuals, extracted from the Linked Open Data provider YAGO. We enriched

    更新日期:2020-09-10
  • LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets
    arXiv.cs.SI Pub Date : 2020-09-08
    Abhilasha Sancheti; Kushal Chawla; Gaurav Verma

    We describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, leveraging both traditional feature-based classifiers as well as recent advances in pre-trained language models that help in capturing the syntactic, semantic, and contextual features from the tweets. We further employ pseudo-labelling

    更新日期:2020-09-10
  • Efficient Quantification of Profile Matching Risk in Social Networks
    arXiv.cs.SI Pub Date : 2020-09-07
    Anisa Halimi; Erman Ayday

    Anonymous data sharing has been becoming more challenging in today's interconnected digital world, especially for individuals that have both anonymous and identified online activities. The most prominent example of such data sharing platforms today are online social networks (OSNs). Many individuals have multiple profiles in different OSNs, including anonymous and identified ones (depending on the

    更新日期:2020-09-10
  • Black Lives Matter discourse on US social media during COVID: polarised positions enacted in a new event
    arXiv.cs.SI Pub Date : 2020-09-08
    Gillian Bolsover

    Black Lives Matter has been a major force for social change in the US since 2014, with social media playing a core role in the development and proliferation of the movement. The largest protests in US history occurred in late May and early June 2020, following the death of George Floyd at the hands of Minneapolis police. This incident reignited widespread support for the BLM movement. The protests

    更新日期:2020-09-10
  • Learning Interpretable Feature Context Effects in Discrete Choice
    arXiv.cs.SI Pub Date : 2020-09-07
    Kiran Tomlinson; Austin R. Benson

    The outcomes of elections, product sales, and the structure of social connections are all determined by the choices individuals make when presented with a set of options, so understanding the factors that contribute to choice is crucial. Of particular interest are context effects, which occur when the set of available options influences a chooser's relative preferences, as they violate traditional

    更新日期:2020-09-10
  • Analysing Twitter Semantic Networks: the case of 2018 Italian Elections
    arXiv.cs.SI Pub Date : 2020-09-07
    Tommaso Radicioni; Elena Pavan; Tiziano Squartini; Fabio Saracco

    Social media play a pivotal role in shaping citizens political opinion. According to the Euro-barometer, the percentage of EU citizens employing online social networks to access information, on a daily basis, has increased from 18% in 2010 to 42% in 2017. The tight entwinement between social media and the unfolding of political dynamics has motivated the interest of researchers for the analysis of

    更新日期:2020-09-08
  • Utilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach
    arXiv.cs.SI Pub Date : 2020-09-06
    Qihang Zhao

    With the advancement of science and technology, the number of academic papers published in the world each year has increased almost exponentially. While a large number of research papers highlight the prosperity of science and technology, they also give rise to some problems. As we all know, academic papers are the most intuitive embodiment of the research results of scholars, which can reflect the

    更新日期:2020-09-08
  • HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process
    arXiv.cs.SI Pub Date : 2020-09-05
    Manisha Dubey; P. K. Srijith; Maunendra Sankar Desarkar

    The prevalence of location-based social networks (LBSNs) has eased the understanding of human mobility patterns. Knowledge of human dynamics can aid in various ways like urban planning, managing traffic congestion, personalized recommendation etc. These dynamics are influenced by factors like social impact, periodicity in mobility, spatial proximity, influence among users and semantic categories etc

    更新日期:2020-09-08
  • Friend Network as Gatekeeper: A Study of WeChat Users' Consumption of Friend-Curated Contents
    arXiv.cs.SI Pub Date : 2020-09-05
    Quan Li; Zhenhui Peng; Haipeng Zeng; Qiaoan Chen; Lingling Yi; Ziming Wu; Xiaojuan Ma; Tianjian Chen

    Social media enables users to publish, disseminate, and access information easily. The downside is that it has fewer gatekeepers of what content is allowed to enter public circulation than the traditional media. In this paper, we present preliminary empirical findings from WeChat, a popular messaging app of the Chinese, indicating that social media users leverage their friend networks collectively

    更新日期:2020-09-08
  • Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
    arXiv.cs.SI Pub Date : 2020-09-07
    Alex Nikolov; Giovanni Da San Martino; Ivan Koychev; Preslav Nakov

    While misinformation and disinformation have been thriving in social media for years, with the emergence of the COVID-19 pandemic, the political and the health misinformation merged, thus elevating the problem to a whole new level and giving rise to the first global infodemic. The fight against this infodemic has many aspects, with fact-checking and debunking false and misleading claims being among

    更新日期:2020-09-08
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