Multidimensional and Multilingual Emotional Analysis

Sofia Aparício; João Tiago Aparício; Manuela Aparício

doi:10.1007/978-3-031-45651-0_2

Multidimensional and Multilingual Emotional Analysis

Sofia Aparício, João Tiago Aparício, Manuela Aparício

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Downloads (Pure)

Abstract

In order to monitor informal political online discussions and to lead a better understanding of hate speech on social media, we found that it was necessary to use sentiment quantification for languages with few training datasets. Previous studies mainly rely on languages with enough data to train a model. Several statistical and machine learning models were produced and compared in three languages (English, Portuguese and Polish). This work shows promising results when inferring sentimental dimensions, even in languages other than English.

Original language	English
Title of host publication	Information Systems and Technologies
Subtitle of host publication	WorldCIST 2023, Volume 4
Editors	Álvaro Rocha, Hojjat Adeli, Gintautas Dzemyda, Fernando Moreira, Valentina Colla
Place of Publication	Gewerbestrasse, Cham
Publisher	Springer
Pages	13-22
Number of pages	10
Volume	4
ISBN (Electronic)	978-3-031-45651-0
ISBN (Print)	978-3-031-45650-3
DOIs	https://doi.org/10.1007/978-3-031-45651-0_2
Publication status	Published - 15 Feb 2024
Event	11th World Conference on Information Systems and Technologies 2023 - Hotel Galilei, Pisa, Italy Duration: 4 Apr 2023 → 6 Apr 2023 Conference number: 11 http://www.worldcist.org/2023/

Publication series

Name	Lecture Notes in Networks and Systems
Publisher	Springer Cham
Volume	802
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	11th World Conference on Information Systems and Technologies 2023
Abbreviated title	WorldCist'23
Country/Territory	Italy
City	Pisa
Period	4/04/23 → 6/04/23
Internet address	http://www.worldcist.org/2023/

Keywords

Emotional ratings of text
Affective norms
Long Short-Term Memory
Recurrent Neural Networks
Machine learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-45651-0_2

Multidimensional_and_Multilingual_Emotional_Analysis_AAMAccepted author manuscript, 718 KBLicence: Unspecified

Cite this

Aparício, Sofia ; Aparício, João Tiago ; Aparício, Manuela. / Multidimensional and Multilingual Emotional Analysis. Information Systems and Technologies: WorldCIST 2023, Volume 4. editor / Álvaro Rocha ; Hojjat Adeli ; Gintautas Dzemyda ; Fernando Moreira ; Valentina Colla. Vol. 4 Gewerbestrasse, Cham : Springer, 2024. pp. 13-22 (Lecture Notes in Networks and Systems).

@inproceedings{922ef2d4084d41af8301a5886a65b904,

title = "Multidimensional and Multilingual Emotional Analysis",

abstract = "In order to monitor informal political online discussions and to lead a better understanding of hate speech on social media, we found that it was necessary to use sentiment quantification for languages with few training datasets. Previous studies mainly rely on languages with enough data to train a model. Several statistical and machine learning models were produced and compared in three languages (English, Portuguese and Polish). This work shows promising results when inferring sentimental dimensions, even in languages other than English.",

keywords = "Emotional ratings of text, Affective norms, Long Short-Term Memory, Recurrent Neural Networks, Machine learning",

author = "Sofia Apar{\'i}cio and Apar{\'i}cio, {Jo{\~a}o Tiago} and Manuela Apar{\'i}cio",

note = "info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT# Apar{\'i}cio, S., Apar{\'i}cio, J. T., & Apar{\'i}cio, M. (2024). Multidimensional and Multilingual Emotional Analysis. In {\'A}. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & V. Colla (Eds.), Information Systems and Technologies: WorldCIST 2023, Volume 4 (Vol. 4, pp. 13-22). (Lecture Notes in Networks and Systems; Vol. 802). Springer. https://doi.org/10.1007/978-3-031-45651-0_2 --- We gratefully acknowledge financial support from FCT -Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia (Portugal), national funding through research grant UIDB/04152/2020. This work is also supported by national funds through PhD grant (UI/BD/153587/2022) supported by FCT.; 11th World Conference on Information Systems and Technologies 2023, WorldCist'23 ; Conference date: 04-04-2023 Through 06-04-2023",

year = "2024",

month = feb,

day = "15",

doi = "10.1007/978-3-031-45651-0_2",

language = "English",

isbn = "978-3-031-45650-3",

volume = "4",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer",

pages = "13--22",

editor = "{\'A}lvaro Rocha and Hojjat Adeli and Gintautas Dzemyda and Fernando Moreira and Valentina Colla",

booktitle = "Information Systems and Technologies",

address = "Netherlands",

url = "http://www.worldcist.org/2023/",

}

Aparício, S, Aparício, JT & Aparício, M 2024, Multidimensional and Multilingual Emotional Analysis. in Á Rocha, H Adeli, G Dzemyda, F Moreira & V Colla (eds), Information Systems and Technologies: WorldCIST 2023, Volume 4. vol. 4, Lecture Notes in Networks and Systems, vol. 802, Springer, Gewerbestrasse, Cham, pp. 13-22, 11th World Conference on Information Systems and Technologies 2023, Pisa, Italy, 4/04/23. https://doi.org/10.1007/978-3-031-45651-0_2

Multidimensional and Multilingual Emotional Analysis. / Aparício, Sofia; Aparício, João Tiago; Aparício, Manuela.
Information Systems and Technologies: WorldCIST 2023, Volume 4. ed. / Álvaro Rocha; Hojjat Adeli; Gintautas Dzemyda; Fernando Moreira; Valentina Colla. Vol. 4 Gewerbestrasse, Cham: Springer, 2024. p. 13-22 (Lecture Notes in Networks and Systems; Vol. 802).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multidimensional and Multilingual Emotional Analysis

AU - Aparício, Sofia

AU - Aparício, João Tiago

AU - Aparício, Manuela

N1 - Conference code: 11

PY - 2024/2/15

Y1 - 2024/2/15

N2 - In order to monitor informal political online discussions and to lead a better understanding of hate speech on social media, we found that it was necessary to use sentiment quantification for languages with few training datasets. Previous studies mainly rely on languages with enough data to train a model. Several statistical and machine learning models were produced and compared in three languages (English, Portuguese and Polish). This work shows promising results when inferring sentimental dimensions, even in languages other than English.

AB - In order to monitor informal political online discussions and to lead a better understanding of hate speech on social media, we found that it was necessary to use sentiment quantification for languages with few training datasets. Previous studies mainly rely on languages with enough data to train a model. Several statistical and machine learning models were produced and compared in three languages (English, Portuguese and Polish). This work shows promising results when inferring sentimental dimensions, even in languages other than English.

KW - Emotional ratings of text

KW - Affective norms

KW - Long Short-Term Memory

KW - Recurrent Neural Networks

KW - Machine learning

UR - https://github.com/keras-team/keras

UR - http://www.scopus.com/inward/record.url?scp=85187665525&partnerID=8YFLogxK

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001259466400002

U2 - 10.1007/978-3-031-45651-0_2

DO - 10.1007/978-3-031-45651-0_2

M3 - Conference contribution

SN - 978-3-031-45650-3

VL - 4

T3 - Lecture Notes in Networks and Systems

SP - 13

EP - 22

BT - Information Systems and Technologies

A2 - Rocha, Álvaro

A2 - Adeli, Hojjat

A2 - Dzemyda, Gintautas

A2 - Moreira, Fernando

A2 - Colla, Valentina

PB - Springer

CY - Gewerbestrasse, Cham

T2 - 11th World Conference on Information Systems and Technologies 2023

Y2 - 4 April 2023 through 6 April 2023

ER -

Multidimensional and Multilingual Emotional Analysis

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this