  This paper presents the HYBRINFOX method used to solve Task 2 of Subjectivity
detection of the CLEF 2024 CheckThat! competition. The specificity of the
method is to use a hybrid system, combining a RoBERTa model, fine-tuned for
subjectivity detection, a frozen sentence-BERT (sBERT) model to capture
semantics, and several scores calculated by the English version of the expert
system VAGO, developed independently of this task to measure vagueness and
subjectivity in texts based on the lexicon. In English, the HYBRINFOX method
ranked 1st with a macro F1 score of 0.7442 on the evaluation data. For the
other languages, the method used a translation step into English, producing
more mixed results (ranking 1st in Multilingual and 2nd in Italian over the
baseline, but under the baseline in Bulgarian, German, and Arabic). We explain
the principles of our hybrid approach, and outline ways in which the method
could be improved for other languages besides English.
