In: Physica A: Statistical Mechanics and its Applications, 2004, vol. 332, p. 519-532
Is visitors’ attendance a fair indicator of a web site's quality? Internet sub-domains are usually characterized by power-law distributions of visits, thus suggesting a rich-get-richer process. If this is the case, the number of visits is not a relevant measure of quality. If, on the other hand, there are active players, i.e., visitors who can tell the value of the information available, better...
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In: Physica A: Statistical and Theoretical Physics, 2007, vol. 373, no. 1, p. 753-758
We develop a simple statistical method to find affinity relations in a large opinion network which is represented by a very sparse matrix. These relations allow us to predict missing matrix elements. We test our method on the Eachmovie data of thousands of movies and viewers. We found that significant prediction precision can be achieved and it is rather stable. There is an intrinsic limit to...
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In: Physics Reports, 2015, vol. 552, p. 1–25
Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the...
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In: Complexity, 2019, vol. 2019, p. 1–17
Understanding and predicting extreme turning points in the financial market, such as financial bubbles and crashes, has attracted much attention in recent years. Experimental observations of the superexponential increase of prices before crashes indicate the predictability of financial extremes. In this study, we aim to forecast extreme events in the stock market using 19-year time-series...
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In: PLoS ONE, 2014, vol. 9, no. 5, p. e96614
Online users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their...
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In: The European Physical Journal B, 2013, vol. 86, no. 2, p. 1-8
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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...
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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...
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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...
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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...
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