Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese

Cristian Muoz Villalobos; Leonardo Alfredo Forero Mendoza; Harold D. De Mello; Marco Pacheco Cavalcanti; Cesar H. Valencia; Alvaro D. Orjuela-Cañon

doi:10.1145/3582768.3582805

Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese

Cristian Muoz Villalobos
, Leonardo Alfredo Forero Mendoza
, Harold D. De Mello
, Marco Pacheco Cavalcanti
, Cesar H. Valencia
, Alvaro D. Orjuela-Cañon

Producción científica: Redes de conocimiento › Actas de congreso

Resumen

Natural Language Processing (NLP) techniques are increasingly powerful for interpreting a person's feelings and reaction to a product or service. Sentiment analysis has become a fundamental tool for this interpretation, and it has studies in languages other than English. This type of application is uncommon and unheard of in Portuguese. This article presents a sentiment analysis classification based on Portuguese social media comments. Representation of word embeddings with both pre-trained Glove and Word2Vec models were generated through a corpus entirely in Portuguese. This article presents a set of results with different models of pre-trained layers and deep learning models exclusive to the Portuguese language on social networks. Two classification models were used and compared: (i) Bidirectional Long Short-Term Memory (BI-LSTM) and (ii) Bidirectional Gated Recurrent Unit (BI-GRU), achieving accuracy results of 99.1

Idioma original	Inglés estadounidense
Páginas	205-209
Número de páginas	5
DOI	https://doi.org/10.1145/3582768.3582805
Estado	Publicada - dic. 16 2022
Evento	6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022 - Bangkok, Tailandia Duración: dic. 16 2022 → dic. 18 2022

Conferencia

Conferencia	6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022
País/Territorio	Tailandia
Ciudad	Bangkok
Período	12/16/22 → 12/18/22

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Áreas temáticas de ASJC Scopus

Interacción persona-ordenador
Redes de ordenadores y comunicaciones
Visión artificial y reconocimiento de patrones
Software

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10.1145/3582768.3582805

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Muoz Villalobos, C., Mendoza, L. A. F., De Mello, H. D., Cavalcanti, M. P., Valencia, C. H., & Orjuela-Cañon, A. D. (2022). Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese. 205-209. Papel presentado en 6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022, Bangkok, Tailandia. https://doi.org/10.1145/3582768.3582805

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title = "Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese",

abstract = "Natural Language Processing (NLP) techniques are increasingly powerful for interpreting a person's feelings and reaction to a product or service. Sentiment analysis has become a fundamental tool for this interpretation, and it has studies in languages other than English. This type of application is uncommon and unheard of in Portuguese. This article presents a sentiment analysis classification based on Portuguese social media comments. Representation of word embeddings with both pre-trained Glove and Word2Vec models were generated through a corpus entirely in Portuguese. This article presents a set of results with different models of pre-trained layers and deep learning models exclusive to the Portuguese language on social networks. Two classification models were used and compared: (i) Bidirectional Long Short-Term Memory (BI-LSTM) and (ii) Bidirectional Gated Recurrent Unit (BI-GRU), achieving accuracy results of 99.1",

author = "\{Muoz Villalobos\}, Cristian and Mendoza, \{Leonardo Alfredo Forero\} and \{De Mello\}, \{Harold D.\} and Cavalcanti, \{Marco Pacheco\} and Valencia, \{Cesar H.\} and Orjuela-Ca{\~n}on, \{Alvaro D.\}",

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Muoz Villalobos, C, Mendoza, LAF, De Mello, HD, Cavalcanti, MP, Valencia, CH & Orjuela-Cañon, AD 2022, 'Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese', Papel presentado en 6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022, Bangkok, Tailandia, 12/16/22 - 12/18/22 pp. 205-209. https://doi.org/10.1145/3582768.3582805

Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese. / Muoz Villalobos, Cristian; Mendoza, Leonardo Alfredo Forero; De Mello, Harold D. et al.
2022. 205-209 Papel presentado en 6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022, Bangkok, Tailandia.

Producción científica: Redes de conocimiento › Actas de congreso

TY - CONF

T1 - Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese

AU - Muoz Villalobos, Cristian

AU - Mendoza, Leonardo Alfredo Forero

AU - De Mello, Harold D.

AU - Cavalcanti, Marco Pacheco

AU - Valencia, Cesar H.

AU - Orjuela-Cañon, Alvaro D.

PY - 2022/12/16

Y1 - 2022/12/16

N2 - Natural Language Processing (NLP) techniques are increasingly powerful for interpreting a person's feelings and reaction to a product or service. Sentiment analysis has become a fundamental tool for this interpretation, and it has studies in languages other than English. This type of application is uncommon and unheard of in Portuguese. This article presents a sentiment analysis classification based on Portuguese social media comments. Representation of word embeddings with both pre-trained Glove and Word2Vec models were generated through a corpus entirely in Portuguese. This article presents a set of results with different models of pre-trained layers and deep learning models exclusive to the Portuguese language on social networks. Two classification models were used and compared: (i) Bidirectional Long Short-Term Memory (BI-LSTM) and (ii) Bidirectional Gated Recurrent Unit (BI-GRU), achieving accuracy results of 99.1

AB - Natural Language Processing (NLP) techniques are increasingly powerful for interpreting a person's feelings and reaction to a product or service. Sentiment analysis has become a fundamental tool for this interpretation, and it has studies in languages other than English. This type of application is uncommon and unheard of in Portuguese. This article presents a sentiment analysis classification based on Portuguese social media comments. Representation of word embeddings with both pre-trained Glove and Word2Vec models were generated through a corpus entirely in Portuguese. This article presents a set of results with different models of pre-trained layers and deep learning models exclusive to the Portuguese language on social networks. Two classification models were used and compared: (i) Bidirectional Long Short-Term Memory (BI-LSTM) and (ii) Bidirectional Gated Recurrent Unit (BI-GRU), achieving accuracy results of 99.1

UR - https://www.scopus.com/pages/publications/85168774760

UR - https://www.scopus.com/pages/publications/85168774760#tab=citedBy

U2 - 10.1145/3582768.3582805

DO - 10.1145/3582768.3582805

M3 - Conference proceedings

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T2 - 6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022

Y2 - 16 December 2022 through 18 December 2022

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Muoz Villalobos C, Mendoza LAF, De Mello HD, Cavalcanti MP, Valencia CH, Orjuela-Cañon AD. Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese. 2022. Papel presentado en 6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022, Bangkok, Tailandia. doi: 10.1145/3582768.3582805

Sentimental Analysis on Social Media Comments with Recurring Models and Pretrained Word Embeddings in Portuguese

Resumen

Conferencia

ODS de las Naciones Unidas

Áreas temáticas de ASJC Scopus

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