Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods

Asian, Jelita; Rosita, Moneyta Dholah; Mantoro, Teddy

doi:10.15575/join.v7i1.900

Cited by 8 publications

(2 citation statements)

References 25 publications

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“…The Multilayer Perceptron is a part of ANN (Artificial Neural Network) that is derived from Perceptron (Asian et al, 2022). It is a feedforward ANN with one or more hidden layers.…”

Section: B Multilayer Perceptronmentioning

confidence: 99%

Analysis of The Multilayer Perceptron Algorithm on Twitter User’s Sentiment Towards The COVID-19 Vaccine

Pasaribu,

Khairina,

Noviandri

et al. 2023

JITE

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The World Health Organization (WHO) declared COVID-19 a global pandemic due to its rapid spread and infection of people worldwide. The emergence of COVID-19 vaccines has garnered both support and rejection from the public. Some people support the vaccines, while others remain cautious, even though the government provides them for free. The procurement of coronavirus vaccines has generated diverse opinions in society. COVID-19 vaccines have become a trending topic on social media, particularly on Twitter. This research aims to explore public opinions on the COVID-19 vaccine. The methods used in this study include data collection, text preprocessing, TF-IDF, multilayer perceptron algorithm, and testing with confusion matrices. Out of a total of 228,208 positive, negative, and neutral opinions from Twitter users about the COVID-19 vaccine, with a training-to-testing ratio of 90% to 100%, the model will learn more by using a large amount of training data. The performance results of this research obtained the highest accuracy of 81.2%, precision of 83.8%, and recall of 71.2%. The results of sentiment analysis can be seen in the public opinions on the COVID-19 vaccine, which are divided into three categories: 35% positive opinions, 16.3% negative opinions, and 48.7% neutral opinions. The word cloud results show that positive opinions revolve around three topics: availability, cost, and dosage. Negative opinions from Twitter users about the COVID-19 vaccine focus on two main issues: vaccine side effects and deaths. Neutral opinions cover three topics, including dosage, availability, age, and expiration date

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“…The Multilayer Perceptron is a part of ANN (Artificial Neural Network) that is derived from Perceptron (Asian et al, 2022). It is a feedforward ANN with one or more hidden layers.…”

Section: B Multilayer Perceptronmentioning

confidence: 99%

Analysis of The Multilayer Perceptron Algorithm on Twitter User’s Sentiment Towards The COVID-19 Vaccine

Pasaribu,

Khairina,

Noviandri

et al. 2023

JITE

View full text Add to dashboard Cite

show abstract

“…The RF method produces better accuracy than the Support Vector Machine (SVM) and logistic regression in classifying feedback and reviewing airline services [31]. An accuracy of 96.42% was obtained by the RF method in classifying public opinion about sexual harassment cases from Brazilian anesthesiologists [5].…”

Section: Introductionmentioning

confidence: 99%

Unbalanced Multiclass Classification With Adaptive Synthetic Multinomial Naive Bayes Approach

Fauzi,

Ismatullah,

Manfaati Nur

2023

IAPGOS

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Opinions related to rising fuel prices need to be seen and analysed. Public opinion is closely related to public policy in Indonesia in the future. Twitter is one of the media that people use to convey their opinions. This study uses sentiment analysis to look at this phenomenon. Sentiment is divided into three categories: positive, neutral, and negative. The methods used in this research are Adaptive Synthetic Multinomial Naive Bayes, Adaptive Synthetic k-nearest neighbours, and Adaptive Synthetic Random Forest. The Adaptive Synthetic method is used to handle unbalanced data. The data used in this study are public arguments per province in Indonesia. The results obtained in this study are negative sentiments that dominate all provinces in Indonesia. There is a relationship between negative sentiment and the level of education, internet use, and the human development index. Adaptive Synthetic Multinomial Naive Bayes performed better than other methods, with an accuracy of 0.882. The highest accuracy of the Adaptive Synthetic Multinomial Naive Bayes method is 0.990 in Papua Barat Province.

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Sentiments analysis of fMRI using automatically generated stimuli labels under naturalistic paradigm

Mahrukh

Shakil

Malik

2023

Sci Rep

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Our emotions and sentiments are influenced by naturalistic stimuli such as the movies we watch and the songs we listen to, accompanied by changes in our brain activation. Comprehension of these brain-activation dynamics can assist in identification of any associated neurological condition such as stress and depression, leading towards making informed decision about suitable stimuli. A large number of open-access functional magnetic resonance imaging (fMRI) datasets collected under naturalistic conditions can be used for classification/prediction studies. However, these datasets do not provide emotion/sentiment labels, which limits their use in supervised learning studies. Manual labeling by subjects can generate these labels, however, this method is subjective and biased. In this study, we are proposing another approach of generating automatic labels from the naturalistic stimulus itself. We are using sentiment analyzers (VADER, TextBlob, and Flair) from natural language processing to generate labels using movie subtitles. Subtitles generated labels are used as the class labels for positive, negative, and neutral sentiments for classification of brain fMRI images. Support vector machine, random forest, decision tree, and deep neural network classifiers are used. We are getting reasonably good classification accuracy (42–84%) for imbalanced data, which is increased (55–99%) for balanced data.

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Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods

Cited by 8 publications

References 25 publications

Analysis of The Multilayer Perceptron Algorithm on Twitter User’s Sentiment Towards The COVID-19 Vaccine

Analysis of The Multilayer Perceptron Algorithm on Twitter User’s Sentiment Towards The COVID-19 Vaccine

Unbalanced Multiclass Classification With Adaptive Synthetic Multinomial Naive Bayes Approach

Sentiments analysis of fMRI using automatically generated stimuli labels under naturalistic paradigm

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