58 citations · 109 across the 6 of their papers we have counts for
6 papers
Managing Bias in Human-Annotated Data: Moving Beyond Bias Removal
Gianluca Demartini, Kevin Roitero, Stefano Mizzaro
Due to the widespread use of data-powered systems in our everyday lives, the notions of bias and fairness gained significant attention among researchers and practitioners, in both…
The Many Dimensions of Truthfulness: Crowdsourcing Misinformation Assessments on a Multidimensional Scale
Michael Soprano, Kevin Roitero, David La Barbera +4
Recent work has demonstrated the viability of using crowdsourcing as a tool for evaluating the truthfulness of public statements. Under certain conditions such as: (1) having a bal…
Can the Crowd Judge Truthfulness? A Longitudinal Study on Recent Misinformation about COVID-19
Kevin Roitero, Michael Soprano, Beatrice Portelli +6
Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd…
Cheap IR Evaluation: Fewer Topics, No Relevance Judgements, and Crowdsourced Assessments
Kevin Roitero
To evaluate Information Retrieval (IR) effectiveness, a possible approach is to use test collections, which are composed of a collection of documents, a set of description of infor…
The COVID-19 Infodemic: Can the Crowd Judge Recent Misinformation Objectively?
Kevin Roitero, Michael Soprano, Beatrice Portelli +5
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large. Very recently, the problem has…
Can The Crowd Identify Misinformation Objectively? The Effects of Judgment Scale and Assessor's Background
Kevin Roitero, Michael Soprano, Shaoyang Fan +3
Truthfulness judgments are a fundamental step in the process of fighting misinformation, as they are crucial to train and evaluate classifiers that automatically distinguish true a…