no code implementations • SemEval (NAACL) 2022 • Tudor Manoleasa, Daniela Gifu, Iustin Sandu
The “iSarcasmEval - Intended Sarcasm Detection in English and Arabic” task at the SemEval 2022 competition focuses on detectingand rating the distinction between intendedand perceived sarcasm in the context of textual sarcasm detection, as well as the level ofirony contained in these texts.
no code implementations • LDL (ACL) 2022 • Fahad Khan, Christian Chiarcos, Thierry Declerck, Maria Pia di Buono, Milan Dojchinovski, Jorge Gracia, Giedre Valunaite Oleskeviciene, Daniela Gifu
This article discusses a survey carried out within the NexusLinguarum COST Action which aimed to give an overview of existing guidelines (GLs) and best practices (BPs) in linguistic linked data.
no code implementations • SEMEVAL 2021 • Mihai Samson, Daniela Gifu
The {``}HaHackathon: Detecting and Rating Humor and Offense{''} task at the SemEval 2021 competition focuses on detecting and rating the humor level in sentences, as well as the level of offensiveness contained in these texts with humoristic tones.
no code implementations • SEMEVAL 2021 • Ciprian Bodnar, Andrada Tapuc, Cosmin Pintilie, Daniela Gifu, Diana Trandabat
This paper presents a word-in-context disambiguation system.
no code implementations • SEMEVAL 2020 • Vlad Ermurachi, Daniela Gifu
The {``}Detection of Propaganda Techniques in News Articles{''} task at the SemEval 2020 competition focuses on detecting and classifying propaganda, pervasive in news article.
no code implementations • LREC 2020 • Adrian Iftene, Daniela Gifu, Andrei-Remus Miron, Mihai-Stefan Dudu
Nowadays, social media credibility is a pressing issue for each of us who are living in an altered online landscape.
no code implementations • SEMEVAL 2019 • Gabriel Florentin Patras, Diana Florina Lungu, Daniela Gifu, Tr, Diana abat
User{'}s content share through social media has reached huge proportions nowadays.
no code implementations • SEMEVAL 2018 • Ramona-Andreea Turcu, Amar, S ei, ra Maria, Iuliana-Alex Flescan-Lovin-Arseni, ra, Daniela Gifu, Tr, Diana abat
The „Affect in Tweets{''} task is centered on emotions categorization and evaluation matrix using multi-language tweets (English and Spanish).