4 research outputs found
Universal hierarchical behavior of citation networks
Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or, in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges implies that citation networks can exhibit hierarchical features that are typical of networks based on decision making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and the various fields display differences only concerning (i)their phase in life (distance from the 'birth' of a field) or (ii)the characteristic time according to which they are approaching the stationary state. We also show by a simple argument that the alterations in the behavior are related to and can be understood by the degree of specialization corresponding to the fields. Our results suggest that during the accumulation of knowledge in a given field, some papers are gradually becoming relatively more influential than most other papers. © 2014 IOP Publishing Ltd and SISSA Medialab srl
Quantitative Determination of Technological Improvement from Patent Data
The results in this paper establish that information contained in patents in a technological domain is strongly correlated with the rate of technological progress in that domain. The importance of patents in a domain, the recency of patents in a domain and the immediacy of patents in a domain are all strongly correlated with increases in the rate of performance improvement in the domain of interest. A patent metric that combines both importance and immediacy is not only highly correlated (r = 0.76, p = 2.6*10[superscript -6]) with the performance improvement rate but the correlation is also very robust to domain selection and appears to have good predictive power for more than ten years into the future. Linear regressions with all three causal concepts indicate realistic value in practical use to estimate the important performance improvement rate of a technological domain.Singapore University of Technology and Desig
Emergence of leader-follower hierarchy among players in an on-line experiment
Hierarchical networks are prevalent in nature and society, corresponding to
groups of actors - animals, humans or even robots - organised according to a
pyramidal structure with decision makers at the top and followers at the
bottom. While this phenomenon is seemingly universal, the underlying governing
principles are poorly understood. Here we study the emergence of hierarchies in
groups of people playing a simple dot guessing game in controlled experiments,
lasting for about 40 rounds, conducted over the Internet. During the games, the
players had the possibility to look at the answer of a limited number of other
players of their choice. This act of asking for advice defines a directed
connection between the involved players, and according to our analysis, the
initial random configuration of the emerging networks became more structured
overt time, showing signs of hierarchy towards the end of the game. In
addition, the achieved score of the players appeared to be correlated with
their position in the hierarchy. These results indicate that under certain
conditions imitation and limited knowledge about the performance of other
actors is sufficient for the emergence of hierarchy in a social group