Autonomous, randomly coupled, neural networks display a transition to chaos at a critical coupling strength. Here, we investigate the effect of a time-varying input on the onset of chaos and the resulting consequences for information processing. Dynamic mean-field theory yields the statistics of the activity, the maximum Lyapunov exponent, and the memory capacity of the network. We find an exact condition that determines the transition from stable to chaotic dynamics and the sequential memory capacity in closed form. The input suppresses chaos by a dynamic mechanism, shifting the transition to significantly larger coupling strengths than predicted by local stability analysis. Beyond linear stability, a regime of coexistent locally expansive but nonchaotic dynamics emerges that optimizes the capacity of the network to store sequential input.
Optimal Sequence Memory in Driven Random Networks
Jannis Schuecker, Sven Goedeke, and Moritz Helias
Phys. Rev. X 8, 041029
Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this article, we mine a massive data set of web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside “social bubbles.”
Nikolov, D.; Lalmas, M.; Flammini, A.; and Menczer, F. Journal of the Association for Information Science and Technology. doi:10.1002/asi.24121 – https://rdcu.be/bbRXl
From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren’t enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models–from linear regression to random walks and far beyond–that can turn anyone into a genius. At the core of the book is Page’s "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
How Can Artificial Life Help Solve Societal Challenges?
Artificial Life has historically been regarded by its adversaries as an academic “hobby” with little relation to real life. We feel that these days are past, as in fact, our interdisciplinary and constantly self-innovating discipline brings together a set of skills and perspectives with a unique potential to tackle some of the most pressing societal challenges of our times. The theme “How can Artificial Life help to solve Societal Challenges” will run through the conference in the shape of keynote presentations and satellite events that apply Artificial Life principles to research on sustainable technologies, bioremediation, urban development and environmental planning, alternative societies a.s.o.But more than merely theming presentations, ALIFE2019 in Newcastle plans to revisit the very way academic conferences are run: a balanced amount of remote talks as well as broadcasting of presentations in order to reduce CO2 emissions, carbon-offset bursaries that allow participants to diminish their ecological footprint, locally sourced catering – these are just a few of the ideas that the organizers will explore, so that us academics can realize some of the change we are advocating for.
July 29-August 2
Newcastle upon Tyne, UK
International mobility facilitates the exchange of scientific, institutional and cultural knowledge. Yet whether globalization and advances in virtual communication technologies have altered the impact of researcher mobility is a relevant and open question that we address by analysing a broad international set of 26 170 physicists from 1980 to 2009, focusing on the 10-year period centred around each mobility event to assess the impact of mobility on research outcomes. We account for secular globalization trends by splitting the analysis into three periods, measuring for each period the effect of mobility on researchers’ citation impact, research topic diversity, collaboration networks and geographical coordination. In order to identify causal effects we leverage statistical matching methods that pair mobile researchers with non-mobile researchers that are similar in research profile attributes prior the mobility event. We find that mobile researchers gain up to a 17% increase in citations relative to their non-mobile counterparts, which can be explained by the simultaneous increase in their diversity of co-authors, topics and geographical coordination in the period immediately following migration. Nevertheless, we also observe that researcher’s completely curtail prior collaborations with their source country in 11% of the cross-border mobility events. As such, these individual-level perturbations fuel multiscale churning in scientific networks, e.g. rewiring the connectivity of individuals and ideas and affecting international integration. Together these results provide additional clarity on the complex relationship between human capital mobility and the dynamics of social capital investment, with implications for immigration and national innovation system policy.
Multiscale impact of researcher mobility
Alexander M. Petersen