Autor: Fortuna, Marcin - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Prosodic typology in light of licensing scales
Autorzy:: Fortuna, Marcin
Tematy:: phonology
CVCV
syllable structure
prosody
typology; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2050931.pdf Link otwiera się w nowym oknie
Opis:: The objective of the paper is to use the model of Complexity Scales and Licensing (Cyran 2003, 2010) to account for the existence of two prosodic types: ‘syllable’ and ‘word’ languages (Auer 1993, Szczepaniak 2007), which roughly correspond to syllable-timed and stress-timed languages. We will postulate that these categories are not primitive and that many of their phonological characteristics can be derived from simpler mechanisms of licensing. It will be also argued that the phenomenon of contrast plays an important role in prosodic typology and may influence syllable structure. Languages use more marked syllabic confi gurations in order to optimise contrast expression. We will carry out an analysis on a simple hypothetical language in order to demonstrate the interdependence of syllabic complexity and the contrastive potential of a syllabic unit.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 2.

Tytuł:: Expert-annotated dataset to study cyberbullying in Polish language
Autorzy:: Pieciukiewicz, Agata
Leliwa, Gniewosz
Wroczynski, Michal
Skrzek, Pawel
Ptaszynski, Michal
Soliwoda, Kamil
Fortuna, Marcin
Dybała, Paweł
Opis:: We introduce the first dataset of harmful and offensive language collected from the Polish Internet. This dataset was meticulously curated to facilitate the exploration of harmful online phenomena such as cyberbullying and hate speech, which have exhibited a significant surge both within the Polish Internet as well as globally. The dataset was systematically collected and then annotated using two approaches. First, it was annotated by two proficient layperson volunteers, operating under the guidance of a specialist in the language of cyberbullying and hate speech. To enhance the precision of the annotations, a secondary round of annotations was carried out by a team of adept annotators with specialized long-term expertise in cyberbullying and hate speech annotations. This second phase was further overseen by an experienced annotator, acting as a super-annotator. In its initial application, the dataset was leveraged for the categorization of cyberbullying instances in the Polish language. Specifically, the dataset serves as the foundation for two distinct tasks: (1) a binary classification that segregates harmful and non-harmful messages and (2) a multi-class classification that distinguishes between two variations of harmful content (cyberbullying and hate speech), as well as a non-harmful category. Alongside the dataset itself, we also provide the models that showed satisfying classification performance. These models are made accessible for third-party use in constructing cyberbullying prevention systems.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego