Big Five Personality Assessment Using KNN method with RoBERTA
Dublin Core
Title
Big Five Personality Assessment Using KNN method with RoBERTA
Subject
Big Five Personality, K-Nearest Neighbours (KNN), RoBERTa, LIWC, Information Gain
Description
Personality is the general way a person responds to and interacts with others. Personality is also often defined as the quality
that distinguishes individuals. Social media was created to help people communicate remotely and easily. These personalities
fall into five categories known as the Big Five personality traits, namely Openness, Conscientiousness, Extraversion,
Agreeableness, and Neuroticism (OCEAN). The use of K-Nearest Neighbour (KNN) is a method of classifying objects based
on the training data closest to them. To overcome the data imbalance during training data, we use K-Means SMOTE (Synthetic
Minority Oversampling Technique). Other features such as LIWC (Linguistic Inquiry Word Count), Information Gain, Robustly
Optimized BERT Approach (RoBERTa), and hyperparameter tuning can improve the performance of the systems we build. The
focus of this study is to present an analysis of Twitter user behavior that can be used to predict the personality of the Big Five
Personality using the KNN method. The Important aspect to consider when using this method, namely accuracy in classifying
the Big Five Personalities. The experimental results show that the accuracy of the KNN method is 72.09%, which is 95.28%
gain above the specified baseline
that distinguishes individuals. Social media was created to help people communicate remotely and easily. These personalities
fall into five categories known as the Big Five personality traits, namely Openness, Conscientiousness, Extraversion,
Agreeableness, and Neuroticism (OCEAN). The use of K-Nearest Neighbour (KNN) is a method of classifying objects based
on the training data closest to them. To overcome the data imbalance during training data, we use K-Means SMOTE (Synthetic
Minority Oversampling Technique). Other features such as LIWC (Linguistic Inquiry Word Count), Information Gain, Robustly
Optimized BERT Approach (RoBERTa), and hyperparameter tuning can improve the performance of the systems we build. The
focus of this study is to present an analysis of Twitter user behavior that can be used to predict the personality of the Big Five
Personality using the KNN method. The Important aspect to consider when using this method, namely accuracy in classifying
the Big Five Personalities. The experimental results show that the accuracy of the KNN method is 72.09%, which is 95.28%
gain above the specified baseline
Creator
Athirah Rifdha Aryani1
, Erwin Budi Setiawan2
, Erwin Budi Setiawan2
Publisher
Universitas Telkom, Bandung
Date
31-10-2022
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Athirah Rifdha Aryani1
, Erwin Budi Setiawan2, “Big Five Personality Assessment Using KNN method with RoBERTA,” Repository Horizon University Indonesia, accessed June 28, 2025, https://repository.horizon.ac.id/items/show/9259.