In: Physics Reports, 2020, vol. 846, p. 1–66
Biological entities are involved in intricate and complex interactions, in which uncovering the biological information from the network concepts are of great significance. Benefiting from the advances of network science and high-throughput biomedical technologies, studying the biological systems from network biology has attracted much attention in recent years, and networks have long been...
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In: Physica A: Statistical Mechanics and its Applications, 2014, vol. 406, p. 139–144
In social sciences, there is currently rare consensus on the underlying mechanism for cultural evolution, partially due to lack of suitable data. The evolution of first names of newborn babies offers a remarkable example for such researches. In this paper, we employ the historical data on baby names from the United States to investigate the evolutionary process of culture, in particular focusing...
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In: Scientific Reports, 2013, vol. 3, p. -
Zipf's law on word frequency and Heaps' law on the growth of distinct words are observed in Indo-European language family, but it does not hold for languages like Chinese, Japanese and Korean. These languages consist of characters, and are of very limited dictionary sizes. Extensive experiments show that: (i) The character frequency distribution follows a power law with exponent close to one, at...
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In: Chinese Physics Letters, 2009, vol. 26, no. 11, p. 118903
Recently, collaborative tagging systems have attracted more and more attention and have been widely applied in web systems. Tags provide highly abstracted information about personal preferences and item content, and therefore have the potential to help in improving better personalized recommendations. We propose a diffusion-based recommendation algorithm considering the personal vocabulary...
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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...
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In: The European Physical Journal B, 2008, vol. 66, no. 4, p. 557-561
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In: The European Physical Journal B, 2008, vol. 66, no. 4, p. 557-561
Keywords in scientific articles have found their significance in information filtering and classification. In this article, we empirically investigated statistical characteristics and evolutionary properties of keywords in a very famous journal, namely Proceedings of the National Academy of Science of the United States of America (PNAS), including frequency distribution, temporal scaling...
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In: Physics Procedia, 2010, vol. 3, no. 5, p. 1877-1885
Recently, social tagging systems have been widely applied in web systems and some physical properties have been found applications in efficiently and effectively personalized recommendation. Social tags can provide highly abstract information about not only item contents but also personalized preferences, hence they might help generate better personalized recommendations. However, how to find out...
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In: Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, no. 23, p. 6100–6106
Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a...
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In: Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, no. 3, p. 647–655
Recently, supply networks have attracted increasing attention from the scientific community. However, it lacks serious consideration of social preference in Supply Chain Management. In this paper, we develop an evolutionary decision-making model to characterize the effects of suppliers’ altruism in supply networks, and find that the performances of both suppliers and supply chains are improved...
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