@inproceedings{GalassiRuggeriBarronCedenoetal., author = {Galassi, Andrea and Ruggeri, Federico and Barr{\´o}n-Cede{\~n}o, Alberto and Alam, Firoj and Caselli, Tommaso and Kutlu, Mucahid and Struß, Julia Maria and Antici, Francesco and Hasanain, Maram and K{\"o}hler, Juliane and Korre, Katerina and Leistra, Folkert and Muti, Arianna and Siegel, Melanie and T{\"u}rkmen, Mehmet Deniz and Wiegand, Michael and Zaghouani, Wajdi}, title = {Overview of the CLEF-2023 CheckThat! Lab: Task 2 on Subjectivity in News Articles}, series = {CLEF 2023 Working Notes}, booktitle = {CLEF 2023 Working Notes}, editor = {Aliannejadi, Mohammad and Faggiolo, Guglielmo and Ferro, Nicola and Vlachos, Michalis}, address = {Thessaloniki}, organization = {Centre for Research and Technology Hellas}, pages = {236 -- 249}, abstract = {We describe the outcome of the 2023 edition of the CheckThat!Lab at CLEF. We focus on subjectivity (Task 2), which has been proposed for the first time. It aims at fostering the technology for the identification of subjective text fragments in news articles. For that, we produced corpora consisting of 9,530 manually-annotated sentences, covering six languages - Arabic, Dutch, English, German, Italian, and Turkish. Task 2 attracted 12 teams, which submitted a total of 40 final runs covering all languages. The most successful approaches addressed the task using state-of-the-art multilingual transformer models, which were fine-tuned on language-specific data. Teams also experimented with a rich set of other neural architectures, including foundation models, zero-shot classifiers, and standard transformers, mainly coupled with data augmentation and multilingual training strategies to address class imbalance. We publicly release all the datasets and evaluation scripts, with the purpose of promoting further research on this topic.}, subject = {Desinformation}, language = {en} }