Identification of emotions on Twitter during the 2022 electoral process in Colombia

The study of Twitter as a means for analyzing social phenomena has gained interest in recent years due to the availability of large amounts of data in a relatively spontaneous environment. Within opinion-mining tasks, emotion detection is specially relevant, as it allows for the identification of pe...

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Autores principales: Iguaran Fernández, Juan José, Pérez, Juan Manuel, Rosati, Germán
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2024
Materias:
Ciencias Informáticas
Emotion Detection
NLP
BERT
LLM
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/177171
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-177171
record_format dspace
spelling I19-R120-10915-1771712025-03-07T20:07:02Z http://sedici.unlp.edu.ar/handle/10915/177171 Identification of emotions on Twitter during the 2022 electoral process in Colombia Iguaran Fernández, Juan José Pérez, Juan Manuel Rosati, Germán 2024-08 2024 2025-03-07T16:26:35Z en Ciencias Informáticas Emotion Detection NLP BERT LLM The study of Twitter as a means for analyzing social phenomena has gained interest in recent years due to the availability of large amounts of data in a relatively spontaneous environment. Within opinion-mining tasks, emotion detection is specially relevant, as it allows for the identification of people’s subjective responses to different social events in a more granular way than traditional sentiment analysis based on polarity. In the particular case of political events, the analysis of emotions in social networks can provide valuable information on the perception of candidates, proposals, and other important aspects of the public debate. In spite of this importance, there are few studies on emotion detection in Spanish and, to the best of our knowledge, few resources are public for opinion mining in Colombian Spanish, highlighting the need for generating resources addressing the specific cultural characteristics of this variety. In this work, we present a small corpus of tweets in Spanish related to the 2022 Colombian presidential elections, manually labeled with emotions using a fine-grained taxonomy. We perform classification experiments using supervised state-of-the-art models (BERT models) and compare them with GPT-3.5 in few-shot learning settings. We make our dataset and code publicly available for research purposes. Sociedad Argentina de Informática e Investigación Operativa Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 60-73
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Emotion Detection
NLP
BERT
LLM
spellingShingle Ciencias Informáticas
Emotion Detection
NLP
BERT
LLM
Iguaran Fernández, Juan José
Pérez, Juan Manuel
Rosati, Germán
Identification of emotions on Twitter during the 2022 electoral process in Colombia
topic_facet Ciencias Informáticas
Emotion Detection
NLP
BERT
LLM
description The study of Twitter as a means for analyzing social phenomena has gained interest in recent years due to the availability of large amounts of data in a relatively spontaneous environment. Within opinion-mining tasks, emotion detection is specially relevant, as it allows for the identification of people’s subjective responses to different social events in a more granular way than traditional sentiment analysis based on polarity. In the particular case of political events, the analysis of emotions in social networks can provide valuable information on the perception of candidates, proposals, and other important aspects of the public debate. In spite of this importance, there are few studies on emotion detection in Spanish and, to the best of our knowledge, few resources are public for opinion mining in Colombian Spanish, highlighting the need for generating resources addressing the specific cultural characteristics of this variety. In this work, we present a small corpus of tweets in Spanish related to the 2022 Colombian presidential elections, manually labeled with emotions using a fine-grained taxonomy. We perform classification experiments using supervised state-of-the-art models (BERT models) and compare them with GPT-3.5 in few-shot learning settings. We make our dataset and code publicly available for research purposes.
format Objeto de conferencia
Objeto de conferencia
author Iguaran Fernández, Juan José
Pérez, Juan Manuel
Rosati, Germán
author_facet Iguaran Fernández, Juan José
Pérez, Juan Manuel
Rosati, Germán
author_sort Iguaran Fernández, Juan José
title Identification of emotions on Twitter during the 2022 electoral process in Colombia
title_short Identification of emotions on Twitter during the 2022 electoral process in Colombia
title_full Identification of emotions on Twitter during the 2022 electoral process in Colombia
title_fullStr Identification of emotions on Twitter during the 2022 electoral process in Colombia
title_full_unstemmed Identification of emotions on Twitter during the 2022 electoral process in Colombia
title_sort identification of emotions on twitter during the 2022 electoral process in colombia
publishDate 2024
url http://sedici.unlp.edu.ar/handle/10915/177171
work_keys_str_mv AT iguaranfernandezjuanjose identificationofemotionsontwitterduringthe2022electoralprocessincolombia
AT perezjuanmanuel identificationofemotionsontwitterduringthe2022electoralprocessincolombia
AT rosatigerman identificationofemotionsontwitterduringthe2022electoralprocessincolombia
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