Misinformation emerges in times of uncertainty when credible information is limited. This is
challenging for NLP-based fact-checking as it relies on counter-evidence, which may not yet …

Several fake claims are commonly repeated over time, especially on social media. To
identify such previous claims, the verified claim retrieval task was studied, where, for a given …

Given the recent proliferation of false claims online, there has been a lot of manual fact-
checking effort. As this is very time-consuming, human fact-checkers can benefit from tools …

In an era where information is quickly shared across many cultural and language contexts,
the neutrality and integrity of news media are essential. Ensuring that media content remains …

As artificial intelligence (AI) has become pervasive in journalistic production, the influence of
algorithms on media practices has grown. We must always consider the interdisciplinary …

A key task in the fact-checking workflow is to establish whether the claim under investigation
has already been debunked or fact-checked before. This is essentially a retrieval task where …

The task of retrieving already debunked narratives aims to detect stories that have already
been fact-checked. The successful detection of claims that have already been debunked not …

In the current era of social media and generative AI, an ability to automatically assess the
credibility of online social media content is of tremendous importance. Credibility …

Fact-checkers are often hampered by the sheer amount of online content that needs to be
fact-checked. NLP can help them by retrieving already existing fact-checks relevant to the …

Pioneer researches recognize evidences as crucial elements in fake news detection apart
from patterns. Existing evidence-aware methods either require laborious pre-processing …