Производительность классификатора

Data acquisition is a major concern in text classification. The excessive human efforts required by conventional methods to build up quality training collection might not always be available to research …...

AbstractThe ability to produce high-quality publishable material is critical to academic success but many Post-Graduate students struggle to learn to do so. While recent years have seen an increase in …...

AbstractAccess to social media often enables users to engage in conversation with limited accountability. This allows a user to share their opinions and ideology, especially regarding public content, occasionally adopting …...

AbstractAbusive language detection has become an important tool for the cultivation of safe online platforms. We investigate the interaction of annotation quality and classifier performance. We use a new, fine-grained …...

AbstractThe spread of COVID-19 misinformation on social media became a major challenge for citizens, with negative real-life consequences. Prior research focused on detection and/or analysis of COVID-19 misinformation. However, fine-grained …...

AbstractThe rapid growth of online communication using social media platforms has led to an increase in the presence of hate speech, especially in terms of sexist language online. The proliferation …...

AbstractWe develop models to classify desirable evidence and desirable reasoning revisions in student argumentative writing. We explore two ways to improve classifier performance – using the essay context of the …...

AbstractThis paper describes the participation of the UMUTeam in the Learning With Disagreements (Le-Wi-Di) shared task proposed at SemEval 2023, which objective is the development of supervised automatic classifiers that …...