Search Results for author:
Found 17 papers, 1 papers with code
The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Media
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.
Demystifying Misconceptions in Social Bots Research
Research on social bots aims at advancing knowledge and providing solutions to one of the most debated forms of online manipulation.
Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence
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.
MulBot: Unsupervised Bot Detection Based on Multivariate Time Series
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.
Personalized Interventions for Online Moderation
Current online moderation follows a one-size-fits-all approach, where each intervention is applied in the same way to all users.
Fine-Grained Prediction of Political Leaning on Social Media with Unsupervised Deep Learning
Here, we propose a novel unsupervised technique for learning fine-grained political leaning from the textual content of social media posts.
Adversarial machine learning for protecting against online manipulation
Adversarial examples are inputs to a machine learning system that result in an incorrect output from that system.
The Spread of Propaganda by Coordinated Communities on Social Media
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.
A Survey on Multimodal Disinformation Detection
As a result, researchers started leveraging different modalities and combinations thereof to tackle online multimodal offensive content.
A Survey on Computational Propaganda Detection
Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda.
A Decade of Social Bot Detection
In this work, we briefly survey the first decade of research in social bot detection.
Towards better social crisis data with HERMES: Hybrid sensing for EmeRgency ManagEment System
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.
The Limited Reach of Fake News on Twitter during 2019 European Elections
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
RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter
We design a novel visualization that we leverage to highlight benign and malicious patterns of retweeting activity.
Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling
We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots.
DNA-inspired online behavioral modeling and its application to spambot detection
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.
Fame for sale: efficient detection of fake Twitter followers
$\textit{Fake followers}$ are those Twitter accounts specifically created to inflate the number of followers of a target account.
