1,721,032 research outputs found
Innovation Poles in Tuscany 2011-2014
No full textThe database "Innovation Poles in Tuscany 2011-2014" collects data on innovation intermediaries, funded through a regional policy intervention, in the Italian region of Tuscany. It has been developed in the research project "Poli.in Analysis and modelling of innovation poles in Tuscany" (www.poliinovazione.unimore.it), co-funded by Tuscany's Regional Administration and University of Modena and Reggio Emilia, Italy. Publications using the present data set are available at www.poliinovazione.unimore.it. The dataset has been already elaborated in - Russo, Margherita, Annalisa Caloffi, Riccardo Righi, Simone Righi, Federica Rossi «Multilayer Network analysis of innovation intermediaries’ activities». In G. Ragozini, M. P. Vitale (eds.), Challenges in Social Network Research, Lecture Notes in Social Networks, © Springer Nature Switzerland AG 2019, https://doi.org/10.1007/978-3-030-31463-7_12 - Russo, Margherita, Annalisa Caloffi, Riccardo Righi, Simone Righi, Federica Rossi. 2016. «Multilayer Network analysis of innovation intermediaries’ activities: methodological issues and an application to a regional policy programme», In Blue Sky Forum: Posters Gallery-Innovation Metrics. Ghent, Belgium. http://www.oecd.org/sti/blue-sky-posters.htm. - Russo, Margherita, Annalisa Caloffi, Federica Rossi, Riccardo Righi. 2018. «Innovation intermediaries and performance-based incentives: a case study of regional innovation poles». Science and Public Policy, 46(1), 2019, 1–12 https://doi.org/10.1093/scipol/scy028. FOLDERS: - folder edges: data on the edgelist in .csv, .dta, .xlsx - folder nodes: data agents in .csv, .dta, .xlsx - folder “graph” : RDS file network in igrap
Review of "Decoding Complexity: Uncovering Patterns in Economic Networks" by James Grattfelder
No full textReview of "Decoding Complexity: Uncovering Patterns in Economic Networks" by James Grattfelde
Evaluating Project Communications with social network Analysis
Full text linkResearch in Social Sciences and Humanities (SSH) has, until recently, tended to evolve under more or less narrow conditions of national cultures and is notably bound to the various countries' languages. Yet the situation is changing: EU Framework Programmes increasingly advance international research collaboration. In addition, particular national policies promoting science and research aim to cross borders as well, e.g. the Austrian Science and Research Liaison Offices (ASO), established and financed by Austrian Ministry of Science and Research. Since 2005 ASO Brno has supported interdisciplinary and trans-border cooperation, involving researchers from Austria, the Czech republic and from other central and south-eastern European countries. In 2007 ASO Brno organized an international workshop to shed lights on communication processes in international research projects. The book assembles presentations from the workshops, supplemented by additional contributions on topics relevant to comprehend and improve conditions, modes, and impact of communication in international SSH research projects
Gossip: Perspective Taking to Establish Cooperation
Full text linkProblems of cooperation are frequent among living organisms, but they are difficult to solve. Humans have been able to produce large-scale cooperation among unrelated individuals through reputation systems. A challenging puzzle, however, is how reputation can guide behavior if in most cases it is not shared publicly and is assigned to others privately. We confirm that it is difficult to obtain cooperation among agents playing the Prisoner’s Dilemma when reputations are individually assigned. We propose that third-party communication (gossip) can overcome this difficulty, but only under specific conditions concerning its content, amount and persistence. We show that—in order to sustain cooperation—gossip should not only be about private evaluations of others but should also include perspective taking and exchange of information about tolerance thresholds to support cooperation. This perspective taking reputational strategy can propagate and establish cooperation in the population independent of gossip frequency and population size, under various selection mechanisms of communication partners and targets, and assumptions concerning agents’ memory
The influence of social network topology in a opinion dynamics model
Full text linkWe investigate an opinion dynamics model with continuously defined affinities and opinions. We focus here on the effects of the affinity matrix's topology on the dynamical evolution and on the scale properties of the model measured through numerical simulations and fittings. We study through a set of statistical network measures, namely mean path, mean degree and clustering, different network topologies. We observe that the model's dynamics eventually leads to a uniformization of the different topologies
How Opinion Dynamics Shapes Social Networks Topology
Full text linkWe investigate an opinion dynamics model with continuously defined affinities and opinions. We focus here on the effects of the social network's topology on the dynamical evolution and on the scale properties of the model measured through numerical simulations and fittings. We study different network topologies through a set of statistical network measures, namely mean path, mean degree and clustering. We observe that the model's dynamics eventually leads to a uniformisation of the different topologies
Face-to-face discussions: networking or opinions exchange?
Full text linkhttps://doi.org/10.1007/978-3-319-00395-5_99We use recent results of [4] on face-to-face contact durations to try to answer the question: why do people engage in face-to-face discussions? In particular we focus on behavior of scientists in academic conferences. We show evidence that macroscopic measured data are compatible with two different micro-founded models of social interaction. We find that the first model, in which discussions are performed with the aim of introducing oneself (networking), explains the data when the group exhibits few well reputed scientists. On the contrary, when the reputation hierarchy is not strong, a model where agents’ encounters are aimed at exchanging opinions explains the data better.We use recent results of [4] on face-to-face contact durations to try to answer
the question: why do people engage in face-to-face discussions? In particular we focus on
behavior of scientists in academic conferences. We show evidence that macroscopic measured
data are compatible with two different micro-founded models of social interaction. We find
that the first model, in which discussions are performed with the aim of introducing oneself
(networking), explains the data when the group exhibits few well reputed scientists. On the
contrary, when the reputation hierarchy is not strong, a model where agents’ encounters are
aimed at exchanging opinions explains the data bette
Quantifying the dynamics of peak disruption in scientific careers
Full text linkWe examine the disruption of researchers with long-lived careers in Computer Science and Physics. Despite the epistemological differences between such disciplines, we consistently find that a researcher’s most disruptive publication does not occur at random during their career, as it cannot be explained by a null model. Such publication is accompanied by a peak year in which researchers publish other work that exhibits a higher level of disruption than average. Through a series of linear models, we show that the disruption achieved by a researcher during their peak year is higher when it is preceded by a long period of focus and low productivity. These findings are in stark contrast with the dynamics of academic impact. In these dynamics, researchers are incentivized by the prevalent paradigms of scientific evaluation to pursue high productivity and incremental - less disruptive - work, as evidenced by extensive literature
Behavioral Biases and Informational Inefficiency in an Agent-Based Financial Market
Full text linkThe role of competitive markets as efficient aggregators of decentralized information is a fundamental problem in economic theory. This paper studies the informational efficiency of a market with a single traded asset, in which agents expectation formation about future price has two kinds of deviations from rationality. First, traders have adaptive expectations, i.e. they give more importance to the past price than a rational agent. Second, the agents are subject to the confirmatory bias, i.e. they tend to discard new information that substantially differs from their priors. Taken separately, each deviation worsens the informational efficiency of the market. However, for some ranges of parameters, when the two biases are combined, they tend to mitigate each other effect (thus increasing the informational efficiency). We also study the robustness of these findings to alternative specifications concerning market participation, entry of new agents, and the amount of liquidity that agents hold.The role of competitive markets as efficient aggregators of decentralized information is a fundamental problem in economic theory. This paper studies the informational efficiency of a market with a single traded asset, in which agents expectation formation about future price has two kinds of deviations from rationality. First, traders have adaptive expectations, i.e. they give more importance to the past price than a rational agent. Second, the agents are subject to the confirmatory bias, i.e. they tend to discard new information that substantially differs from their priors. Taken separately, each deviation worsens the informational efficiency of the market. However, for some ranges of parameters, when the two biases are combined, they tend to mitigate each other effect (thus increasing the informational efficiency). We also study the robustness of these findings to alternative specifications concerning market participation, entry of new agents, and the amount of liquidity that agents hold
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