To scale the size of Information Retrieval collections, crowdsourcing has become a common way to collect relevance judgments at scale. Crowdsourcing experiments usually employ …
Due to the increasing amount of information shared online every day, the need for sound and reliable ways of distinguishing between trustworthy and non-trustworthy information is …
Conference Talk - The 15th ACM International Conference on Web Search and Data Mining (WSDM 2022). February 23, 2022, Phoenix, U.S.A. (remote). Held remotely as a pre-recorded …
Due to their relatively low cost and ability to scale, crowdsourcing based approaches are widely used to collect a large amount of human annotated data. To this aim, multiple …
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 …
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 …
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 …
Conference Talk - The 29th ACM International Conference on Information and Knowledge Management (CIKM 2020). October 19, 2020, Galway, Ireland (remote). Held remotely as a …
Conference Talk - The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020). July 25, 2020, Xi'an, China (remote). Held remotely …
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 …