Université de Fribourg

Model-based evaluation of scientific impact indicators

Medo, Matúš ; Cimini, Giulio

In: Physical Review E, 2016, vol. 94, no. 3, p. 032312

Using bibliometric data artificially generated through a model of citation dynamics calibrated on empirical data, we compare several indicators for the scientific impact of individual researchers. The use of such a controlled setup has the advantage of avoiding the biases present in real databases, and it allows us to assess which aspects of the model dynamics and which traits of individual...

Université de Fribourg

Network-driven reputation in online scientific communities

Liao, Hao ; Xiao, Rui ; Cimini, Giulio ; Medo, Matúš

In: PLoS ONE, 2014, vol. 9, no. 12, p. e112022

The ever-increasing quantity and complexity of scientific production have made it difficult for researchers to keep track of advances in their own fields. This, together with growing popularity of online scientific communities, calls for the development of effective information filtering tools. We propose here an algorithm which simultaneously computes reputation of users and fitness of papers in...

Université de Fribourg

Adaptive social recommendation in a multiple category landscape

Chen, Duanbing ; Zeng, An ; Cimini, Giulio ; Zhang, Yi-Cheng

In: The European Physical Journal B, 2013, vol. 86, no. 2, p. 1–8

People in the Internet era have to cope with the information overload, striving to find what they are interested in, and usually face this situation by following a limited number of sources or friends that best match their interests. A recent line of research, namely adaptive social recommendation, has therefore emerged to optimize the information propagation in social networks and provide users...

Université de Fribourg

Enhancing topology adaptation in information-sharing social networks

Cimini, Giulio ; Chen, Duanbing ; Medo, Matúš ; Lü, Linyuan ; Zhang, Yi-Cheng ; Zhou, Tao

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2012, vol. 85, no. 4, p. 046108

The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an...

Université de Fribourg

Removing spurious interactions in complex networks

Zeng, An ; Cimini, Giulio

In: Physical Review E - Statistical, nonlinear, and soft matter physics, 2012, vol. 85, no. 3, p. 036101

Identifying and removing spurious links in complex networks is meaningful for many real applications and is crucial for improving the reliability of network data, which, in turn, can lead to a better understanding of the highly interconnected nature of various social, biological, and communication systems. In this paper, we study the features of different simple spurious link elimination methods,...

Université de Fribourg

Temporal effects in the growth of networks

Medo, Matúš ; Cimini, Giulio ; Gualdi, Stanislao

In: Physical Review Letters, 2011, vol. 107, no. 23, p. 238701

We show that to explain the growth of the citation network by preferential attachment (PA), one has to accept that individual nodes exhibit heterogeneous fitness values that decay with time. While previous PA-based models assumed either heterogeneity or decay in isolation, we propose a simple analytically treatable model that combines these two factors. Depending on the input assumptions, the...

Université de Fribourg

Heterogeneity, quality, and reputation in an adaptive recommendation model

Cimini, Giulio ; Medo, Matúš ; Zhou, Tao ; Wei, Dong ; Zhang, Yi-Cheng

In: The European Physical Journal B - Condensed Matter and Complex Systems, 2011, vol. 80, no. 2, p. 201-208

Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a “good get richer” feature of the model and determine which attributes are necessary...

Université de Fribourg

Emergence of scale-free leadership structure in social recommender systems

Zhou, Tao ; Medo, Matúš ; Cimini, Giulio ; Zhang, Zi-Ke ; Zhang, Yi-Cheng

In: PLoS ONE, 2011, vol. 6, no. 7, p. e20648

The study of the organization of social networks is important for the understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this...

Université de Fribourg

Effective mechanism for social recommendation of news

Wei, Dong ; Zhou, Tao ; Cimini, Giulio ; Wu, Pei ; Liu, Weiping ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, no. 11, p. 2117-2126

Recommender systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize the network’s topology we propose different stochastic...