Information spread, influence and attention

We build theoretical models to investigate how content gets online attention, who adopts it, and who can influence the process.

Causal Inference: A basic taster

An introduction to the core motivation, underlying theory and practical methodology of causal inference through examples.

evently: simulation, fitting of Hawkes processes

We introduce evently, an R package designed for simulating and fitting the Hawkes processes and the HawkesN processes.

Disinformation and online problematic content

We develop methods to detect and address weaponised disinformation and problematic content (hate speech, misinformation, conspiracy theories, anti-minority rhetoric).

birdspotter: A toolkit for analyzing and labelling Twitter users

We introduce birdspotter, an R tool that models Twitter users’ attributes and labels them.

User Analysis on reshare cascades about COVID-19

In this tutorial, we apply two novel tools (BirdSpotter and Evently) for analyzing Twitter users on a COVID-19 retweet dataset.

The labour markets of tomorrow

Our research proposes adaptative and personalised methods to help workers transition into new occupations by accounting for their experience and personality profiles.

Job Transitions in a Time of Automation and Labour Market Crises

We build a machine learning-based recommender system that can accurately predict the probability of transitioning between occupations.