activity
20142023
most citedVEWS: A Wikipedia Vandal Early Warning System

90 citations · 102 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2023

Evaluating Code Metrics in GitHub Repositories Related to Fake News and Misinformation

Jason Duran, Mostofa Sakib, Nasir Eisty +1

The surge of research on fake news and misinformation in the aftermath of the 2016 election has led to a significant increase in publicly available source code repositories. Our st…

cs.IR2018★ 1 cited

Who is Really Affected by Fraudulent Reviews? An analysis of shilling attacks on recommender systems in real-world scenarios

Anu Shrestha, Francesca Spezzano, Maria Soledad Pera

We present the results of an initial analysis conducted on a real-life setting to quantify the effect of shilling attacks on recommender systems. We focus on both algorithm perform…

cs.SI2015★ 90 cited

VEWS: A Wikipedia Vandal Early Warning System

Srijan Kumar, Francesca Spezzano, V. S. Subrahmanian

We study the problem of detecting vandals on Wikipedia before any human or known vandalism detection system reports flagging potential vandals so that such users can be presented e…

cs.LO2014

ChoiceGAPs: Competitive Diffusion as a Massive Multi-Player Game in Social Networks

Edoardo Serra, Francesca Spezzano, V. S. Subrahmanian

We consider the problem of modeling competitive diffusion in real world social networks via the notion of ChoiceGAPs which combine choice logic programs due to Sacca` and Zaniolo a…

cs.LO2014★ 11 cited

Checking Termination of Bottom-Up Evaluation of Logic Programs with Function Symbols

Marco Calautti, Sergio Greco, Francesca Spezzano +1

Recently, there has been an increasing interest in the bottom-up evaluation of the semantics of logic programs with complex terms. The presence of function symbols in the program m…