RT Dissertation/Thesis
T1 Technologies for extracting and analysing the credibility of health-related online content
A1 Fernández Pichel, Marcos
K1 Health misinformation
K1 Web Search
K1 Information Retrieval
K1 Natural Language Processing
AB The evolution of the Web has led to an improvement ininformation accessibility. This change has allowed access tomore varied content at greater speed, but we must also beaware of the dangers involved. The results offered may beunreliable, inadequate, or of poor quality, leading tomisinformation. This can have a greater or lesser impactdepending on the domain, but is particularly sensitive when itcomes to health-related content.In this thesis, we focus in the development of methods toautomatically assess credibility. We also studied the reliability ofthe new Large Language Models (LLMs) to answer healthquestions. Finally, we also present a set of tools that might helpin the massive analysis of web textual content.
YR 2023
FD 2023
LK http://hdl.handle.net/10347/32483
UL http://hdl.handle.net/10347/32483
LA eng
DS Minerva
RD 30 abr 2026