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

Autor

Cesar Hernando Valencia
Cristian Muoz Villalobos
Harold D. De Mello
Leonardo Alfredo Forero Mendoza
Marco Pacheco Cavalcanti

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

autores

http://vivoweb.org/ontology/core#FacultyMember
Orjuela Cañón, Alvaro David

fecha de publicación

2022-12-16

Área temática

Salud y bienestar

Identificador de objeto digital (DOI)

https://doi.org/10.1145/3582768.3582805

Número de páginas

5

Página inicial

205

Última página

209