no code implementations • 3 Jan 2024 • John Bianchi, Manuel Pratelli, Marinella Petrocchi, Fabio Pinelli
The proliferation of low-quality online information in today's era has underscored the need for robust and automatic mechanisms to evaluate the trustworthiness of online news publishers.
no code implementations • 15 Apr 2023 • Edoardo Di Paolo, Marinella Petrocchi, Angelo Spognardi
Online Social Networks have revolutionized how we consume and share information, but they have also led to a proliferation of content not always reliable and accurate.
no code implementations • 30 Mar 2023 • Stefano Cresci, Kai-Cheng Yang, Angelo Spognardi, Roberto Di Pietro, Filippo Menczer, Marinella Petrocchi
Research on social bots aims at advancing knowledge and providing solutions to one of the most debated forms of online manipulation.
no code implementations • 5 May 2022 • Manuel Pratelli, Marinella Petrocchi
In today's era of information disorder, many organizations are moving to verify the veracity of news published on the web and social media.
no code implementations • 23 Nov 2021 • Stefano Cresci, Marinella Petrocchi, Angelo Spognardi, Stefano Tognazzi
Adversarial examples are inputs to a machine learning system that result in an incorrect output from that system.
no code implementations • 26 Jan 2021 • Alessandro Balestrucci, Rocco De Nicola, Marinella Petrocchi, Catia Trubiani
Thanks to platforms such as Twitter and Facebook, people can know facts and events that otherwise would have been silenced.
Social and Information Networks
no code implementations • 27 Dec 2020 • Michela Fazzolari, Francesco Buccafurri, Gianluca Lax, Marinella Petrocchi
Over the last years, online reviews became very important since they can influence the purchase decision of consumers and the reputation of businesses, therefore, the practice of writing fake reviews can have severe consequences on customers and service providers.
no code implementations • 10 Apr 2018 • Fabio Del Vigna, Marinella Petrocchi, Alessandro Tommasi, Cesare Zavattari, Maurizio Tesconi
However, being the collaborative web characterised by a redundancy of information, it is not unusual that the same fact is reported by multiple sources, which may not apply the same restriction policies in terms of censorship.
no code implementations • 21 Jul 2017 • Michela Fazzolari, Vittoria Cozza, Marinella Petrocchi, Angelo Spognardi
In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score.
no code implementations • 18 Apr 2017 • Michela Fazzolari, Marinella Petrocchi, Alessandro Tommasi, Cesare Zavattari
In this paper, we propose a novel approach for aggregating online reviews, according to the opinions they express.
no code implementations • 13 Mar 2017 • Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, Maurizio Tesconi
We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots.
no code implementations • 21 Sep 2016 • Fabio Del Vigna, Marinella Petrocchi, Alessandro Tommasi, Cesare Zavattari, Maurizio Tesconi
Based on the very small set of initial seeds, the work highlights how a contrastive approach and context deduction are effective in detecting substances and effects from the corpora.
no code implementations • 7 Mar 2016 • Vittoria Cozza, Marinella Petrocchi, Angelo Spognardi
We move from the intuition that the quality of content of medical Web documents is affected by features related with the specific domain.
no code implementations • 30 Jan 2016 • Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, Maurizio Tesconi
We propose a strikingly novel, simple, and effective approach to model online user behavior: we extract and analyze digital DNA sequences from user online actions and we use Twitter as a benchmark to test our proposal.
no code implementations • 14 Sep 2015 • Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, Maurizio Tesconi
$\textit{Fake followers}$ are those Twitter accounts specifically created to inflate the number of followers of a target account.