This paper describes the participation of the UniOR NLP Research Group team in task 3 (T3) within the CLEF eRisk 2021 lab. We report the approaches used to address eRisk 2021 T3, which aims to measure the severity of the signs of depression in social media users. This year’s eRisk T3 consists of exploring methods for automatically filling out a 21-question depression questionnaire, namely Beck’s Depression Inventory (BDI). We explored and tried different combinations of text pre-processing and feature extraction steps in order to grasp self-referential pieces of text and two main methods for representing the text features as input data for traditional machine learning classifiers.

UniOR NLP at eRisk 2021: Assessing the Severity of Depression with Part of Speech and Syntactic Features

Raffaele Manna;Johanna Monti
2021-01-01

Abstract

This paper describes the participation of the UniOR NLP Research Group team in task 3 (T3) within the CLEF eRisk 2021 lab. We report the approaches used to address eRisk 2021 T3, which aims to measure the severity of the signs of depression in social media users. This year’s eRisk T3 consists of exploring methods for automatically filling out a 21-question depression questionnaire, namely Beck’s Depression Inventory (BDI). We explored and tried different combinations of text pre-processing and feature extraction steps in order to grasp self-referential pieces of text and two main methods for representing the text features as input data for traditional machine learning classifiers.
2021
Inglese
AA.VV
Guglielmo Faggioli, Nicola Ferro, Alexis Joly, Maria Maistro, Florina Piroi
Conference and Labs of the Evaluation Forum Proceedings
contributo
CLEF 2021 – Conference and Labs of the Evaluation Forum
2936
1022
1030
9
https://ceur-ws.org/Vol-2936/
CEUR
Esperti anonimi
September 21–24, 2021
Bucharest, Romania
Internazionale
Natural Language Processing, Machine Learning, Topic Modeling, Sentence Embeddings, Mental Health Risk Assessment
2
Manna, Raffaele; Monti, Johanna
open
273
info:eu-repo/semantics/conferenceObject
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
File in questo prodotto:
File Dimensione Formato  
paper-82.pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: PUBBLICO - Pubblico con Copyright
Dimensione 495.6 kB
Formato Adobe PDF
495.6 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11574/219622
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact