no code implementations • 16 Dec 2023 • Amaury Trujillo, Tiziano Fagni, Stefano Cresci
They offer guidance for future regulations that cater to the reporting needs of online platforms in general, but also highlight opportunities to improve and refine the database itself.
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 • 17 Jan 2023 • Serena Tardelli, Leonardo Nizzoli, Maurizio Tesconi, Mauro Conti, Preslav Nakov, Giovanni Da San Martino, Stefano Cresci
Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior.
no code implementations • 21 Sep 2022 • Lorenzo Mannocci, Stefano Cresci, Anna Monreale, Athina Vakali, Maurizio Tesconi
Not only does MulBot achieve excellent results in the binary classification task, but we also demonstrate its strengths in a novel and practically-relevant task: detecting and separating different botnets.
no code implementations • 19 May 2022 • Stefano Cresci, Amaury Trujillo, Tiziano Fagni
Current online moderation follows a one-size-fits-all approach, where each intervention is applied in the same way to all users.
no code implementations • 23 Feb 2022 • Tiziano Fagni, Stefano Cresci
Here, we propose a novel unsupervised technique for learning fine-grained political leaning from the textual content of social media posts.
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 • 27 Sep 2021 • Kristina Hristakieva, Stefano Cresci, Giovanni Da San Martino, Mauro Conti, Preslav Nakov
Large-scale manipulations on social media have two important characteristics: (i) use of propaganda to influence others, and (ii) adoption of coordinated behavior to spread it and to amplify its impact.
no code implementations • COLING 2022 • Firoj Alam, Stefano Cresci, Tanmoy Chakraborty, Fabrizio Silvestri, Dimiter Dimitrov, Giovanni Da San Martino, Shaden Shaar, Hamed Firooz, Preslav Nakov
As a result, researchers started leveraging different modalities and combinations thereof to tackle online multimodal offensive content.
no code implementations • 15 Jul 2020 • Giovanni Da San Martino, Stefano Cresci, Alberto Barron-Cedeno, Seunghak Yu, Roberto Di Pietro, Preslav Nakov
Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda.
no code implementations • 23 Jun 2020 • Stefano Cresci
In this work, we briefly survey the first decade of research in social bot detection.
no code implementations • 4 Dec 2019 • Marco Avvenuti, Salvatore Bellomo, Stefano Cresci, Leonardo Nizzoli, Maurizio Tesconi
People involved in mass emergencies increasingly publish information-rich contents in online social networks (OSNs), thus acting as a distributed and resilient network of human sensors.
1 code implementation • 27 Nov 2019 • Matteo Cinelli, Stefano Cresci, Alessandro Galeazzi, Walter Quattrociocchi, Maurizio Tesconi
The advent of social media changed the way we consume content favoring a disintermediated access and production.
Social and Information Networks Computers and Society Physics and Society
no code implementations • 12 Feb 2019 • Michele Mazza, Stefano Cresci, Marco Avvenuti, Walter Quattrociocchi, Maurizio Tesconi
We design a novel visualization that we leverage to highlight benign and malicious patterns of retweeting activity.
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 • 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.