Search Results for author:
Found 5 papers, 2 papers with code
Multi-Aspect Transfer Learning for Detecting Low Resource Mental Disorders on Social Media
We propose that transfer learning with linguistic features can be useful for approaching both the technical problem of improving mental disorder detection in the context of data scarcity, and the clinical problem of understanding the overlapping symptoms between certain disorders.
Understanding Patterns of Anorexia Manifestations in Social Media Data with Deep Learning
Eating disorders are a growing problem especially among young people, yet they have been under-studied in computational research compared to other mental health disorders such as depression.
SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification
The paper describes the SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (MAMI), which explores the detection of misogynous memes on the web by taking advantage of available texts and images.
Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains
This paper presents the overview of the AuTexTification shared task as part of the IberLEF 2023 Workshop in Iberian Languages Evaluation Forum, within the framework of the SEPLN 2023 conference.
Fake News and Hate Speech: Language in Common
In this paper we raise the research question of whether fake news and hate speech spreaders share common patterns in language.
