13 citations · 13 across the 7 of their papers we have counts for
7 papers
Prompt-based mental health screening from social media text
Wesley Ramos dos Santos, Ivandre Paraboni
This article presents a method for prompt-based mental health screening from a large and noisy dataset of social media text. Our method uses GPT 3.5. prompting to distinguish publi…
UstanceBR: a social media language resource for stance prediction
Camila Pereira, Matheus Pavan, Sungwon Yoon +4
This work introduces UstanceBR, a multimodal corpus in the Brazilian Portuguese Twitter domain for target-based stance prediction. The corpus comprises 86.8 k labelled stances towa…
Text and author-level political inference using heterogeneous knowledge representations
Samuel Caetano da Silva, Ivandre Paraboni
The inference of politically-charged information from text data is a popular research topic in Natural Language Processing (NLP) at both text- and author-level. In recent years, st…
Myers-Briggs personality classification from social media text using pre-trained language models
Vitor Garcia dos Santos, Ivandré Paraboni
In Natural Language Processing, the use of pre-trained language models has been shown to obtain state-of-the-art results in many downstream tasks such as sentiment analysis, author…
Personality facets recognition from text
Wesley Ramos dos Santos, Ivandre Paraboni
Fundamental Big Five personality traits (e.g., Extraversion) and their facets (e.g., Activity) are known to correlate with a broad range of linguistic features and, accordingly, th…
Semi-automatic definite description annotation: a first report
Danillo da Silva Rocha, Alex Gwo Jen Lan, Ivandre Paraboni
Studies in Referring Expression Generation (REG) often make use of corpora of definite descriptions produced by human subjects in controlled experiments. Experiments of this kind,…
Trainable Referring Expression Generation using Overspecification Preferences
Thiago castro Ferreira, Ivandre Paraboni
Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may othe…