121 citations · 198 across the 9 of their papers we have counts for
10 papers
Dynamics of Algorithmic Content Amplification on TikTok
Fabian Baumann, Nipun Arora, Iyad Rahwan +1
Intelligent algorithms increasingly shape the content we encounter and engage with online. TikTok's For You feed exemplifies extreme algorithm-driven curation, tailoring the stream…
Mutual benefits of social learning and algorithmic mediation for cumulative culture
Agnieszka Czaplicka, Fabian Baumann, Iyad Rahwan
The remarkable ecological success of humans is often attributed to our ability to develop complex cultural artefacts that enable us to cope with environmental challenges. The evolu…
Machine Culture
Levin Brinkmann, Fabian Baumann, Jean-François Bonnefon +12
The ability of humans to create and disseminate culture is often credited as the single most important factor of our success as a species. In this Perspective, we explore the notio…
Network Structure shapes the Impact of Diversity in Collective Learning
Fabian Baumann, Agnieszka Czaplicka, Iyad Rahwan
It is widely believed that diversity arising from different skills enhances the performance of teams, and in particular, their ability to learn and innovate. However, diversity has…
Biased-voter model: how persuasive a small group can be?
Agnieszka Czaplicka, Christos Charalambous, Raul Toral +1
We study the voter model dynamics in the presence of confidence and bias. We assume two types of voters. Unbiased voters whose confidence is indifferent to the state of the voter a…
From equality to diversity -- bottom-up approach for hierarchy growth
Agnieszka Czaplicka, Janusz A. Hołyst
The hierarchical topology is a common property of many complex systems. Here we introduce a simple but generic model of hierarchy growth from the bottom to the top. Therein, two dy…
Competition of simple and complex adoption on interdependent networks
Agnieszka Czaplicka, Raul Toral, Maxi San Miguel
We consider the competition of two mechanisms for adoption processes: a so-called complex threshold dynamics and a simple Susceptible-Infected-Susceptible (SIS) model. Separately,…
Coevolution of Information Processing and Topology in Hierarchical Adaptive Random Boolean Networks
Piotr J. Gorski, Agnieszka Czaplicka, Janusz A. Holyst
Random Boolean networks (RBNs) are frequently employed for modelling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a h…
Information slows down hierarchy growth
Agnieszka Czaplicka, Krzysztof Suchecki, Borja Minano +2
We consider models of growing multi-level systems wherein the growth process is driven by rules of tournament selection. A system can be conceived as an evolving tree with a new no…
Emotional agents at the square lattice
Agnieszka Czaplicka, Anna M. Chmiel, Janusz A. Holyst
We introduce and investigate by numerical simulations a number of models of emotional agents at the square lattice. Our models describe the most general features of emotions such a…