A survey of sentiment analysis in the Portuguese language

Pereira, Denilson Alves

doi:10.1007/s10462-020-09870-1

Cited by 62 publications

(46 citation statements)

References 60 publications

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“…For the sentiment analysis, we identified the polarity of the opinion or emotion expressed in the texts. One challenge we faced was the lack of robust language resources to support sentiment analysis for the Portuguese language [ 41 ]. This is due to the lack of advanced tools for Portuguese.…”

Section: Methodsmentioning

confidence: 99%

Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach

Melo¹,

Figueiredo²

2021

JMIR Public Health Surveill

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Background The COVID-19 pandemic is severely affecting people worldwide. Currently, an important approach to understand this phenomenon and its impact on the lives of people consists of monitoring social networks and news on the internet. Objective The purpose of this study is to present a methodology to capture the main subjects and themes under discussion in news media and social media and to apply this methodology to analyze the impact of the COVID-19 pandemic in Brazil. Methods This work proposes a methodology based on topic modeling, namely entity recognition, and sentiment analysis of texts to compare Twitter posts and news, followed by visualization of the evolution and impact of the COVID-19 pandemic. We focused our analysis on Brazil, an important epicenter of the pandemic; therefore, we faced the challenge of addressing Brazilian Portuguese texts. Results In this work, we collected and analyzed 18,413 articles from news media and 1,597,934 tweets posted by 1,299,084 users in Brazil. The results show that the proposed methodology improved the topic sentiment analysis over time, enabling better monitoring of internet media. Additionally, with this tool, we extracted some interesting insights about the evolution of the COVID-19 pandemic in Brazil. For instance, we found that Twitter presented similar topic coverage to news media; the main entities were similar, but they differed in theme distribution and entity diversity. Moreover, some aspects represented negative sentiment toward political themes in both media, and a high incidence of mentions of a specific drug denoted high political polarization during the pandemic. Conclusions This study identified the main themes under discussion in both news and social media and how their sentiments evolved over time. It is possible to understand the major concerns of the public during the pandemic, and all the obtained information is thus useful for decision-making by authorities.

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Section: Methodsmentioning

confidence: 99%

Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach

Melo¹,

Figueiredo²

2021

JMIR Public Health Surveill

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“…Na língua portuguesa, essas duas tarefas são tratadas por uma quantidade muito menor de trabalhos, que em geral apresentam métodos baseados em léxicos e ontologias para tratar as tarefas individualmente [16]. Porém, existem trabalhos que tratam a identificação de subjetividade e polaridade no âmbito da aprendizagem de máquina, como Moraes et al [14] e Britto e Pacífico [4].…”

Section: Classificação De Subjetividade E Polaridadeunclassified

“…Devido à relevância das duas tarefas de análise de sentimentos, existem muitos trabalhos que tratam destas duas tarefas em textos em inglês [18,19,23]. Porém, ainda existe necessidade de mais investigação em outros idiomas, como o português [3,16]. A falta de ferramentas de processamento de texto e de dados anotados para experimentos figuram como desafios para a análise de sentimentos neste idioma.…”

Section: Introductionunclassified

“…A falta de ferramentas de processamento de texto e de dados anotados para experimentos figuram como desafios para a análise de sentimentos neste idioma. Além disso, conforme reportado por Pereira [16], ainda há muito espaço para o desenvolvimento de métodos de análise de sentimentos para a língua portuguesa que explorem especificidades linguísticas.…”

Section: Introductionunclassified

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Investigating sets of linguistic features for two sentiment analysis tasks in Brazilian Portuguese web reviews

Oliveira¹,

Melo²

2020

Anais Estendidos Do XXVI Simpósio Brasileiro De Sistemas Multimídia E Web (WebMedia 2020)

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Identifying subjective sentences and classifying the polarity of subjective sentences are two important tasks in sentiment analysis. Besides being a hot topic, there is still a lack of resources to perform the mentioned sentiment analysis tasks in the Portuguese language, with its syntactic specificities. This paper describes the identified challenges and next steps in an initial study regarding the classification of subjectivity and polarity of sentences with a small set of syntactic features extracted directly from the text. Our approach reached satisfying results in experiments with two classic machine learning models in four datasets consisting of user reviews from different domains.

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“…Aspect Extraction (AE) is the first part of the ABSA. It is a key task, as errors in this step generate errors in the next step (Aspect Sentiment Classification) (Pereira, 2020). This phase consists of the identification of the parts of the text that represent entity's aspects.…”

Section: Introductionmentioning

confidence: 99%

Exploring BERT for Aspect Extraction in Portuguese Language

Lopes

Corrêa

Freitas

2021

FLAIRS

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Sentiment Analysis is the computer science field that comprises techniques that aim to automatically extract opinions from texts. Usually, these techniques assign a Sentiment Orientation to the whole document (Document Level Sentiment Analysis). But a document can express sentiment about several aspects of an entity. Methods that extract those aspects, paired with the sentiment about them, operate in the Aspect Level. Aspect-Based Sentiment Analysis approaches can be split into two stages: Aspect Extraction and Aspect Sentiment Classification. The literature presents works mainly focused on reviews about hotels, smartphones, or restaurants. In this work, we present an approach for Aspect Extraction based on Multilingual (Google's) and Portuguese (BERTimbau) BERT pre-trained models. Our experiments show that Aspect Extraction based on BERT pre-trained for Portuguese achieved Balanced Accuracy of up to 93% on a corpus of reviews about the accommodation sector.

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A survey of sentiment analysis in the Portuguese language

Cited by 62 publications

References 60 publications

Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach

Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach

Investigating sets of linguistic features for two sentiment analysis tasks in Brazilian Portuguese web reviews

Exploring BERT for Aspect Extraction in Portuguese Language

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