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

Research output: Knowledge networksConference proceedings

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

Original languageEnglish (US)
Pages205-209
Number of pages5
DOIs
StatePublished - Dec 16 2022
Event6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022 - Bangkok, Thailand
Duration: Dec 16 2022Dec 18 2022

Conference

Conference6th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2022
Country/TerritoryThailand
CityBangkok
Period12/16/2212/18/22

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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