Mindenkit szeretettel várunk az MTA TK "Lendület" RECENS hálózati előadás-sorozatának következő alkalmára 2016. április 5-én (kedden), melyen Roberta Sinatra (CEU CNS) tart előadást "Quantifying patterns of scientific success” címmel.
Az előadás megrendezésére az MTA TK Politikatudományi Intézetének tárgyalótermében (1014 Budapest, Országház utca 30.) kerül sor 15 órai kezdettel.
Az előadás kivonata:
Our current approach to understanding success is driven by the belief that predicting exceptional impact requires us to detect extraordinary ability. Despite the long-standing interest in the problem, we still lack a clear understanding of how performance emerges and evolves in time.
In contrast to individual ability, we quantify and model success as a collective phenomenon: for something to be successful, it is not enough to be novel or appealing, but we all must agree that it is worthy of praise. If we accept the collective nature of success, its signatures can be uncovered from the many pieces of data around us using the tools of network and data sciences. In this talk I will focus on individual impact in science as a way for testing our ability to measure and predict success. By studying changes in individual productivity and impact, as measured by influential publications, I will show that impact is distributed randomly within a scientist’s sequence of publications. This random impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, skill and luck, unveils the existence of universal patterns governing the emergence of scientific success and allows to accurately predict the evolution of a scientist’s impact indicators, from the h-index to cumulative citations.
The uncovered patterns point towards a general, quantitative theory of success, that can offer actionable information towards a quantitative evaluation and prediction of impact dynamics in different contexts, from science and arts to entrepreneurial activities and software development.
Bio:
Roberta Sinatra is Assistant Professor at the Center for Network Science and at the Math Department, Central European University (Hungary), and a visiting Faculty at the Network Science Institute, Northeastern University (USA). She is a theoretical physicist by training, working at the forefront of network and data science, developing novel theoretical methods and analyzing empirical data sets on social phenomena and human behavior. Currently, she spends particular attention on the analysis and the modeling of information and dynamics that lead to the collective phenomenon of success. Roberta completed her studies in Physics at the University of Catania, Italy, and spent time as a visiting research student in Universities and Research centers in Zaragoza (Spain), London (UK), and Vienna (Austria). In 2012 she joined the BarabasiLab in Boston, first as Postdoctoral fellow, then starting 2014 as Research Assistant Professor. She has won several awards and grants, in particular a 3-years fellowship by the James S. McDonnell Foundation and a grant from the AirForce for the study of scientific success.