@article{eprints2839,
           pages = {201--208},
           title = {Heterogeneity, quality, and reputation in an adaptive recommendation model},
            year = {2011},
          volume = {80},
          author = {Giulio Cimini and Mat{\'u}{\v s} Medo and Tao Zhou and Dong Wei and Yi-Cheng Zhang},
         journal = {The European Physical Journal B - Condensed Matter},
       publisher = {Springer},
          number = {2},
        keywords = {Physics and society, Social and information networks},
        abstract = {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 for a user to play a leading role in the network. We further investigate the filtering efficiency of the model as well as its robustness against malicious and spamming behaviour. We show that incorporating user reputation in the recommendation process can substantially improve the outcome.},
             url = {http://eprints.imtlucca.it/2839/}
}