Recommender systems are quickly becoming ubiquitous in many Web applications, including e-commerce, social media channels, content providers, among others. These systems act as an enabling mechanism designed to overcome the information overload problem by improving browsing and consumption experience. Crucial to the performance of a recommender system is the accuracy of the user profiles used to represent the interests of the users. In this proposal, we analyze three different aspects of user profiling: (i) selecting the most informative events from the interaction between users and the system, (ii) combining different recommendation algorithms to (iii) including trust-aware information in user profiles to improve the accuracy of recommender systems.
Reputation is a key social construct in science. However, the relation between this key signaling credential and career growth remains poorly understood. Here we develop an original framework for measuring how citation paths are shaped by two distinct factors - the scientific merit of each individual paper versus the reputation of its authors within the scientific community. To estimate the relative influence of these two factors we perform a longitudinal analysis of publication data for 450 leading scientists from biology, physics, and mathematics. Our panel data approach quantifies the role of social ties, author reputation, and the citation life cycle of individual papers. We uncover statistical regularities in the coevolution of publications and citations, which we use as benchmarks to test and validate a stochastic model for the citation dynamics governing a scientists publication portfolio. We find strong evidence of increasing returns to scale in the growth of both publications and citations, reflecting the amplifying role of social processes. Moreover, our analysis shows that author reputation dominates in the initial phase of a papers citation life cycle. This latter result suggests that papers gain a significant early citation advantage if written by authors already having high reputations in the scientific community. As quantitative measures become increasingly common in the evaluation of scientific careers, our results show that the use of measures that do not account for reputation effects may paradoxically counteract the goal of sustaining talented and diligent young academics.
The authors: "We believe the basic mechanisms of reputation signaling in social networks are quite general, and so it is likely that reputation plays a similar role in other recommender systems which pervade diverse online socio-technical systems characterized by generic diffusion and contagion phenomena. Our results on the respective roles of author reputation and
paper impact on citations unravel an important mechanism contributing to the stratification of scientific communities. In particular, they provide a rationale for young scientists being attracted to work in teams led by leaders in the scientific community."
Reputation and Impact in Academic CareersAlexander M. Petersen, Santo Fortunato, Raj K. Pan, Kimmo Kaski, Orion Penner, Massimo Riccaboni, H. Eugene Stanley, Fabio Pammolli(Submitted on 29 Mar 2013)arXiv.org > physics > arXiv:1303.7274
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