Search Results for author:
Found 5 papers, 3 papers with code
Cascade-based Echo Chamber Detection
Experiments on synthetic data show that our algorithm is able to correctly reconstruct ground-truth latent communities with their degree of echo-chamber behavior and opinion polarity.
On learning agent-based models from data
In this paper, we propose a protocol to learn the latent micro-variables of an ABM from data.
Learning Ideological Embeddings from Information Cascades
Modeling information cascades in a social network through the lenses of the ideological leaning of its users can help understanding phenomena such as misinformation propagation and confirmation bias, and devising techniques for mitigating their toxic effects.
Learning Opinion Dynamics From Social Traces
In this work we propose an inference mechanism for fitting a generative, agent-like model of opinion dynamics to real-world social traces.
Estimating latent feature-feature interactions in large feature-rich graphs
Other authors, instead, developed more sophisticated models, that are able to handle complex feature interactions, but are unfit to scale to very large networks.
