loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ricardo Martins ; José João Almeida ; Pedro Henriques and Paulo Novais

Affiliation: Department of Informatics, Algoritmi Centre, University of Minho, Braga, Portugal

Keyword(s): Sentiment Analysis, Natural Language Processing, Machine Learning.

Abstract: According to the World Health Organization (WHO), close to 300 million people of all ages suffer from depression. Also, for WHO, depression is the leading reason for disability worldwide and is a major contributor to the global burden of disease. Different than the mood fluctuation raised by the common life’s activities, depression can be a serious health problem, particularly when it is a long-term and mid/high intensity. Luckily, despite depression is a silent disease, people when suffering leaves some clues. Due to the massive use of social media, these clues can be collected through the texts posted on social media, such as Twitter, Facebook, Instagram, and later, analysed to identify if the writing style matches with a depressive pattern. This paper presents an approach that can be applied by Machine Learning models to help psychologists to identify depressive clues in texts. The model examines profiles on Twitter based on clues provided by users in their posts. Combining Sentim ent Analysis, Machine Learning and Natural Language Processing techniques, we achieved a precision of 98% by Machine Learning models when identifying Twitter profiles that post potential depressive texts. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.203.235.24

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Martins, R.; Almeida, J.; Henriques, P. and Novais, P. (2021). Identifying Depression Clues using Emotions and AI. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 1137-1143. DOI: 10.5220/0010332811371143

@conference{icaart21,
author={Ricardo Martins. and José João Almeida. and Pedro Henriques. and Paulo Novais.},
title={Identifying Depression Clues using Emotions and AI},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={1137-1143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010332811371143},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Identifying Depression Clues using Emotions and AI
SN - 978-989-758-484-8
IS - 2184-433X
AU - Martins, R.
AU - Almeida, J.
AU - Henriques, P.
AU - Novais, P.
PY - 2021
SP - 1137
EP - 1143
DO - 10.5220/0010332811371143
PB - SciTePress