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...

Université de Fribourg

Degree correlation of bipartite network on personalized recommendation

Liu, Jian-Guo ; Zhou, Tao ; Zhang, Yi-Cheng ; Guo, Qiang

In: International Journal of Modern Physics C, 2010, vol. 21, no. 1, p. 137-147

In this paper, the statistical property, namely degree correlation between users and objects, is taken into account and be embedded into the similarity index of collaborative filtering (CF) algorithm to improve the algorithmic performance. The numerical simulation on a benchmark data set shows that the algorithmic accuracy of the presented algorithm, measured by the average ranking score, is...

Université de Fribourg

Effects of user's tastes on personalized recommendation

Liu, Jian-Guo ; Zhou, Tao ; Wang, Bing-Hong ; Zhang, Yi-Cheng ; Guo, Qiang

In: International Journal of Modern Physics C, 2009, vol. 20, no. 12, p. 1925-1932

In this paper, based on a weighted projection of the user-object bipartite network, we study the effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected. We argue that the initial recommendation power located on the objects should be determined by both of their...

Université de Fribourg

Evolution characteristics of the network core in the facebook

Liu, Jian-Guo ; Ren, Zhuo-Ming ; Guo, Qiang ; Chen, Duan-Bing

In: PLoS ONE, 2014, vol. 9, no. 8, p. e104028

Statistical properties of the static networks have been extensively studied. However, online social networks are evolving dynamically, understanding the evolving characteristics of the core is one of major concerns in online social networks. In this paper, we empirically investigate the evolving characteristics of the Facebook core. Firstly, we separate the Facebook-link(FL) and Facebook-wall(FW)...

Université de Fribourg

Evolution properties of online user preference diversity

Guo, Qiang ; Ji, Lei ; Liu, Jian-Guo ; Han, Jingti

In: Physica A: Statistical Mechanics and its Applications, 2017, vol. 468, p. 698–713

Detecting the evolution properties of online user preference diversity is of significance for deeply understanding online collective behaviors. In this paper, we empirically explore the evolution patterns of online user rating preference, where the preference diversity is measured by the variation coefficient of the user rating sequence. The statistical results for four real systems show...

Université de Fribourg

Evolution properties of the community members for dynamic networks

Yang, Kai ; Guo, Qiang ; Li, Sheng-Nan ; Han, Jing-Ti ; Liu, Jian-Guo

In: Physics Letters A, 2017, vol. 381, no. 11, p. 970–975

The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities...

Université de Fribourg

Heat conduction information filtering via local information of bipartite networks

Guo, Qiang ; Leng, R. ; Shi, K. ; Liu, J.G.

In: The European Physical Journal B - Condensed Matter and Complex Systems, 2012, vol. 85, no. 8, p. 286

Information filtering based on structure properties of user-object bipartite networks is of both theoretical interest and practical significance in modern science. In this paper, we empirically investigate the framework of heat-conduction-based (HC) information filtering [Y.-C. Zhang et al., Phys. Rev. Lett. 99, 154301 (2007)] in terms of the local node similarity. We compare nine well-known...

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...

Université de Fribourg

Identifying online user reputation of user–object bipartite networks

Liu, Xiao-Lu ; Liu, Jian-Guo ; Yang, Kai ; Guo, Qiang ; Han, Jing-Ti

In: Physica A: Statistical Mechanics and its Applications, 2017, vol. 467, p. 508–516

Identifying online user reputation based on the rating information of the user–object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part...

Consortium of Swiss Academic Libraries

Improved collaborative filtering algorithm based on heat conduction

Guo, Qiang ; Liu, Jianguo ; Wang, Binghong

In: Frontiers of Computer Science in China, 2009, vol. 3, no. 3, p. 417-420