Detecting addiction, anxiety, and depression by users psychometric profiles

Autor: Anna Monreale, Benedetta Iavarone, Elena Rossetto, Andrea Beretta

Publikováno v: WWW '22-The ACM Web Conference 2022, pp. 1189–1197, Virtual Event, Lyon France, 25-29/04/2022

Detecting and characterizing people with mental disorders is an important task that could help the work of different healthcare professionals. Sometimes, a diagnosis for specific mental disorders requires a long time, possibly causing problems becaus

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9576c7e16efff01bf26bb05cf93697aa
https://openportal.isti.cnr.it/doc?id=people______::51bc41e85397bdd9ad948507b85de716

Predicting movie-elicited emotions from dialogue in screenplay text: A study on 'Forrest Gump'

Autor: Felice Dell'Orletta, Benedetta Iavarone

Publikováno v: Scopus-Elsevier
CLiC-it

We present a new dataset of sentences extracted from the movie Forrest Gump, annotated with the emotions perceived by a group of subjects while watching the movie. We run experiments to predict these emotions using two classifiers, one based on a Sup

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55e83a9c2e8afc65519e7bcae53fa29a
http://books.openedition.org/aaccademia/8610

Is this Sentence Difficult? Do you Agree?

Autor: Felice Dell'Orletta, Lorenzo De Mattei, Benedetta Iavarone, Giulia Venturi, Dominique Brunato

Publikováno v: EMNLP
Scopus-Elsevier
Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1–10, Brussels, 31/10/2018-04/11/2018
info:cnr-pdr/source/autori:Brunato D., De Mattei L., Dell'Orletta F., Iavarone B., Venturi G./congresso_nome:Conference on Empirical Methods in Natural Language Processing (EMNLP)/congresso_luogo:Brussels/congresso_data:31%2F10%2F2018-04%2F11%2F2018/anno:2018/pagina_da:1/pagina_a:10/intervallo_pagine:1–10

In this paper, we present a crowdsourcing-based approach to model the human perception of sentence complexity. We collect a large corpus of sentences rated with judgments of complexity for two typologically-different languages, Italian and English. W

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b20afe55a6629fdb761a47415ea243ae
https://doi.org/10.18653/v1/d18-1289