activity
20182021
most citedLeveraging Contextual Embeddings for Detecting Diachronic Semantic Shift

42 citations · 56 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SI20219 cited

Online Hate: Behavioural Dynamics and Relationship with Misinformation

Matteo Cinelli, Andraž Pelicon, Igor Mozetič +3

Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making n…

cs.SI2021

Community evolution in retweet networks

Bojan Evkoski, Igor Mozetic, Nikola Ljubesic +1

Communities in social networks often reflect close social ties between their members and their evolution through time. We propose an approach that tracks two aspects of community e…

cs.CY20195 cited

(Mis)Information Operations: An Integrated Perspective

Matteo Cinelli, Mauro Conti, Livio Finos +6

The massive diffusion of social media fosters disintermediation and changes the way users are informed, the way they process reality, and the way they engage in public debate. The…

cs.CL201942 cited

Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift

Matej Martinc, Petra Kralj Novak, Senja Pollak

We propose a new method that leverages contextual embeddings for the task of diachronic semantic shift detection by generating time specific word representations from BERT embeddin…

cs.SI2018

Forex trading and Twitter: Spam, bots, and reputation manipulation

Igor Mozetič, Peter Gabrovšek, Petra Kralj Novak

Currency trading (Forex) is the largest world market in terms of volume. We analyze trading and tweeting about the EUR-USD currency pair over a period of three years. First, a larg…