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Université de Fribourg

Social signature identification of dynamical social networks

Li, Ren-De ; Liu, Jian-Guo ; Guo, Qiang ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2018, vol. 508, p. 213–222

Understanding the social relation of dynamical online social networks (OSNs) is significant for identifying the strong and weak ties. In this paper, we empirically investigate the evolution characteristics of Facebook and Wiki users’ social signature, capturing the distribution of frequency of interactions between different alters over time in ego network. The statistical results show that...

Université de Fribourg

Structure-oriented prediction in complex networks

Ren, Zhuo-Ming ; Zeng, An ; Zhang, Yi-Cheng

In: Physics Reports, 2018, vol. 750, p. 1–51

Complex systems are extremely hard to predict due to its highly nonlinear interactions and rich emergent properties. Thanks to the rapid development of network science, our understanding of the structure of real complex systems and the dynamics on them has been remarkably deepened, which meanwhile largely stimulates the growth of effective prediction approaches on these systems. In this...

Université de Fribourg

Enhancing countries’ fitness with recommender systems on the international trade network

Liao, Hao ; Huang, Xiao-Min ; Wu, Xing-Tong ; Liu, Ming-Kai ; Vidmer, Alexandre ; Zhou, Ming-Yang ; Zhang, Yi-Cheng

In: Complexity, 2018, p. -

Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries’ data of the International Trade Network. A recommendation system is then...

Université de Fribourg

Randomizing growing networks with a time-respecting null model

Ren, Zhuo-Ming ; Mariani, Manuel Sebastian ; Zhang, Yi-Cheng ; Medo, Matú?

In: Physical Review E, 2018, vol. 97, no. 5, p. 052311

Complex networks are often used to represent systems that are not static but grow with time: People make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of measurements made on such networks, we propose a randomization methodology—a time- respecting null model—that preserves both the network's degree sequence...

Université de Fribourg

Collective iteration behavior for online social networks

Liu, Jian-Guo ; Li, Ren-De ; Guo, Qiang ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2018, vol. 499, p. 490–497

Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users’ online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the...

Consortium of Swiss Academic Libraries

Predicting missing links via local information

Zhou, Tao ; Lü, Linyuan ; Zhang, Yi-Cheng

In: The European Physical Journal B, 2009, vol. 71, no. 4, p. 623-630

Université de Fribourg

Uncovering the popularity mechanisms for Facebook applications

Li, Sheng-Nan ; Guo, Qiang ; Yang, Kai ; Liu, Jian-Guo ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2018, vol. 494, p. 422–429

Understanding the popularity dynamics of online application(App) is significant for the online social systems. In this paper, by dividing the Facebook Apps into different groups in terms of their popularities, we empirically investigate the popularity dynamics for different kinds of Facebook Apps. Then, taking into account the influence of cumulative and recent popularities on the user...

Université de Fribourg

Identifying online user reputation in terms of user preference

Dai, Lu ; Guo, Qiang ; Liu, Xiao-Lu ; Liu, Jian-Guo ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2018, vol. 494, p. 403–409

Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users...