Assessing Italian News Reliability in the Health Domain through Text Analysis of Headlines

Luca Giordano, Maria Pia Di Buono

Abstract:

Fake news detection and fact checking represent challenging research areas in Natural
Language Processing (NLP), especially in the
health domain, which presents specific characteristics to be dealt with. On the one hand,
online sources have become one of the main
channels to retrieve health-related information.
On the other hand, most of the time such online information suffers from lack of quality
and requires domain-specific knowledge to be
assessed. Therefore, the spread of untrustworthy health-related content urges to be mitigated
since it may represent a threat for lives.
To this aim, we develop a domain-specific annotated dataset suitable for training automatic
systems to assess Italian news reliability. Our
proposal tries to overcome some of the limitations of the available datasets by applying
an in-depth text analysis to obtain a more finegrained reliability assessment in the health domain.