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Université de Fribourg

Link prediction in bipartite nested networks

Medo, Matúš ; Mariani, Manuel Sebastian ; Lü, Linyuan

In: Entropy, 2018, vol. 20, no. 10, p. 777

Real networks typically studied in various research fields—ecology and economic complexity, for example—often exhibit a nested topology, which means that the neighborhoods of high-degree nodes tend to include the neighborhoods of low-degree nodes. Focusing on nested networks, we study the problem of link prediction in complex networks, which aims at identifying likely candidates for...

Consortium of Swiss Academic Libraries

The effect of the initial network configuration on preferential attachment

Berset, Yves ; Medo, Matúš

In: The European Physical Journal B, 2013, vol. 86, no. 6, p. 1-7

Université de Fribourg

Ranking in evolving complex networks

Liao, Hao ; Mariani, Manuel Sebastian ; Medo, Matúš ; Zhang, Yi-Cheng ; Zhou, Ming-Yang

In: Physics Reports, 2017, vol. 689, p. 1–54

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are...

Université de Fribourg

Information filtering based on corrected redundancy-eliminating mass diffusion

Zhu, Xuzhen ; Yang, Yujie ; Chen, Guilin ; Medo, Matúš ; Tian, Hui ; Cai, Shi-Min

In: PLOS ONE, 2017, vol. 12, no. 7, p. e0181402

Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects’ attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is...

Université de Fribourg

Quantifying and suppressing ranking bias in a large citation network

Vaccario, Giacomo ; Medo, Matúš ; Wider, Nicolas ; Mariani, Manuel Sebastian

In: Journal of Informetrics, 2017, vol. 11, no. 3, p. 766–782

It is widely recognized that citation counts for papers from different fields cannot be directly compared because different scientific fields adopt different citation practices. Citation counts are also strongly biased by paper age since older papers had more time to attract citations. Various procedures aim at suppressing these biases and give rise to new normalized indicators, such as the...

Université de Fribourg

Identification and impact of discoverers in online social systems

Medo, Matúš ; Mariani, Manuel S. ; Zeng, An ; Zhang, Yi-Cheng

In: Scientific Reports, 2016, vol. 6, p. 34218

Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by...

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

Study of market model describing the contrary behaviors of informed and uninformed agents: Being minority and being majority

Zhang, Yu-Xia ; Liao, Hao ; Medo, Matúš ; Shang, Ming-Sheng ; Yeung, Chi Ho

In: Physica A: Statistical Mechanics and its Applications, 2016, vol. 450, p. 486–496

In this paper we analyze the contrary behaviors of the informed investors and uniformed investors, and then construct a competition model with two groups of agents, namely agents who intend to stay in minority and those who intend to stay in majority. We find two kinds of competitions, inter- and intra-groups. The model shows periodic fluctuation feature. The average distribution of...

Université de Fribourg

Ranking nodes in growing networks: When PageRank fails

Mariani, Manuel Sebastian ; Medo, Matúš ; Zhang, Yi-Cheng

In: Scientific Reports, 2015, vol. 5, p. 16181

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s...

Université de Fribourg

Prediction in complex systems: the case of the international trade network

Vidmer, Alexandre ; Zeng, An ; Medo, Matúš ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2015, vol. 436, p. 188–199

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the...