Journal ArticleDOI
Investigating Link Inference in Partially Observable Networks: Friendship Ties and Interaction
TLDR
The results suggest that interactions reiterate the information contained in friendship ties sufficiently well to serve as a proxy when the majority of a network is unobserved.Abstract:
While privacy preserving mechanisms, such as hiding one’s friends list, may be available to withhold personal information on online social networking sites, it is not obvious whether to which degree a user’s social behavior renders such an attempt futile. In this paper, we study the impact of additional interaction information on the inference of links between nodes in partially covert networks. This investigation is based on the assumption that interaction might be a proxy for connectivity patterns in online social networks. For this purpose, we use data collected from 586 Facebook profiles consisting of friendship ties (conceptualized as the network) and comments on wall posts (serving as interaction information) by a total of 64 000 users. The link-inference problem is formulated as a binary classification problem using a comprehensive set of features and multiple supervised learning algorithms. Our results suggest that interactions reiterate the information contained in friendship ties sufficiently well to serve as a proxy when the majority of a network is unobserved.read more
Citations
More filters
Journal ArticleDOI
Medical cyber-physical systems: A survey.
TL;DR: This article enriched the researches of the networked Medical Device (MD) systems to increase the efficiency and safety of the healthcare.
Journal ArticleDOI
A Hybrid Privacy Protection Scheme in Cyber-Physical Social Networks
TL;DR: This work proposes a hybrid privacy-preserving scheme, which considers both location and identity privacy against a dynamic adversary, and establishes a game-based Markov decision process model, in which the user and the adversary are regarded as two players in a dynamic multistage zero-sum game.
Journal ArticleDOI
PersoNet: Friend Recommendation System Based on Big-Five Personality Traits and Hybrid Filtering
TL;DR: This paper presents and evaluates an FRS based on the big-five personality traits model and hybrid filtering, in which the friend recommended process is based on personality traits and users’ harmony rating and shows that PersoNet performs better than collaborative filtering (CF)-based FRS in terms of precision and recall.
Journal ArticleDOI
Data-driven computational social science : A survey
TL;DR: A survey on data-driven computational social science for the first time which primarily focuses on reviewing application domains involving human dynamics is presented in this article, where the state-of-the-art research on human dynamics are reviewed from three aspects: individuals, relationships, and collectives.
Journal ArticleDOI
3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks
TL;DR: Experimental results indicate that the proposed three-level hidden Bayesian link prediction model can not only mine user latent interest distribution but also can improve the performance of link prediction effectively.
References
More filters
Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI
Fast unfolding of communities in large networks
Vincent D. Blondel,Jean-Loup Guillaume,Jean-Loup Guillaume,Renaud Lambiotte,Renaud Lambiotte,Etienne Lefebvre +5 more
TL;DR: This work proposes a heuristic method that is shown to outperform all other known community detection methods in terms of computation time and the quality of the communities detected is very good, as measured by the so-called modularity.
Journal ArticleDOI
Fast unfolding of communities in large networks
Vincent D. Blondel,Jean-Loup Guillaume,Jean-Loup Guillaume,Renaud Lambiotte,Renaud Lambiotte,Etienne Lefebvre +5 more
TL;DR: In this paper, the authors proposed a simple method to extract the community structure of large networks based on modularity optimization, which is shown to outperform all other known community detection methods in terms of computation time.
Journal IssueDOI
The link-prediction problem for social networks
David Liben-Nowell,Jon Kleinberg +1 more
TL;DR: Experiments on large coauthorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
{SNAP Datasets}: {Stanford} Large Network Dataset Collection
Jure Leskovec,Andrej Krevl +1 more
TL;DR: A collection of more than 50 large network datasets from tens of thousands of node and edges to tens of millions of nodes and edges that includes social networks, web graphs, road networks, internet networks, citation networks, collaboration networks, and communication networks.