Applying Answer Set Programming for Knowledge-Based Link Prediction on Social Interaction Networks [0.03%]
基于知识库的社交交互网络链接预测的答案集编程方法研究
Çiçek Güven,Martin Atzmueller
Çiçek Güven
Link prediction targets the prediction of possible future links in a social network, i. e., we aim to predict the next most likely links of the network given the current state. However, predicting the future solely based on (scarce) histori...
Anna Sapienza,Palash Goyal,Emilio Ferrara
Anna Sapienza
Cooperation is a fundamental social mechanism, whose effects on human performance have been investigated in several environments. Online games are modern-days natural settings in which cooperation strongly affects human behavior. Every day,...
Alexandra Olteanu,Carlos Castillo,Fernando Diaz et al.
Alexandra Olteanu et al.
Social data in digital form-including user-generated content, expressed or implicit relations between people, and behavioral traces-are at the core of popular applications and platforms, driving the research agenda of many researchers. The ...
Identifying Travel Regions Using Location-Based Social Network Check-in Data [0.03%]
基于位置的社交网络签到数据的旅游地区识别
Avradip Sen,Linus W Dietz
Avradip Sen
Travel regions are not necessarily defined by political or administrative boundaries. For example, in the Schengen region of Europe, tourists can travel freely across borders irrespective of national borders. Identifying transboundary trave...
Calum Thornhill,Quentin Meeus,Jeroen Peperkamp et al.
Calum Thornhill et al.
Fake news is increasingly an issue on social media platforms. In this work, rather than detect misinformation, we propose the use of nudges to help steer internet users into fact checking the news they read online. We discuss two types of n...
Swarna Das,Md Musfique Anwar
Swarna Das
Community detection is an interesting field of online social networks. Most existing approaches either consider common attributes of social network users or rely on only social connections among the users. However, not enough attention is p...
An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks [0.03%]
基于多层网络的 twitter 主题驱动型互动模型
Obaida Hanteer,Luca Rossi
Obaida Hanteer
We propose a way to model topic-based implicit interactions among Twitter users. Our model relies on grouping Twitter hashtags, in a given context, into themes/topics and then using the multiplex network model to construct a thematic multip...
Abusive Language Detection in Online Conversations by Combining Content- and Graph-Based Features [0.03%]
融合内容和图特征的在线对话谩骂语言检测方法研究
Noé Cécillon,Vincent Labatut,Richard Dufour et al.
Noé Cécillon et al.
In recent years, online social networks have allowed world-wide users to meet and discuss. As guarantors of these communities, the administrators of these platforms must prevent users from adopting inappropriate behaviors. This verification...
You Can't See Me: Anonymizing Graphs Using the Szemerédi Regularity Lemma [0.03%]
隐身术：利用Szemerédi规则引理匿名化图数据
Daniele Foffano,Luca Rossi,Andrea Torsello
Daniele Foffano
Complex networks gathered from our online interactions provide a rich source of information that can be used to try to model and predict our behavior. While this has very tangible benefits that we have all grown accustomed to, there is a co...
Shagun Sodhani,Meng Qu,Jian Tang
Shagun Sodhani
Network embedding, which aims at learning distributed representations for nodes in networks, is a critical task with wide downstream applications. Most existing studies focus on networks with a single type of edges, whereas in many cases, t...