Optimization Prediction of Big Five Personality in Twitter Users
Dublin Core
Title
Optimization Prediction of Big Five Personality in Twitter Users
Subject
Big Five Personality, SVM, TF-IDF, LIWC, Optimization
Description
Various kinds of information can be acquired from social media platforms; one of them is on Twitter. User biographical
information and tweets are the essential assets for research that can describe the Big Five Personality, including openness,
conscientiousness, extraversion, agreeableness, and neuroticism. Several previous studies have tried the prediction of Big Five
Personality. However, the authors found problems in how to optimize the work of the personality prediction system. So, in this
study, Big Five Personality predictions were carried out on users of Twitter and improved the performance of the personality
prediction system. We implement optimization techniques such as sampling, feature selection, and hyperparameter tuning to
enhance the performance. This study also applies linguistic feature extraction, such as LIWC and TF-IDF. By using 287 Twitter
users that have permitted their data to be crawled acquired from an online survey using Big Five Inventory (BFI), and applying
all optimization techniques, the average accuracy result is 84.22% which is a 74.44% gain over the specified baseline.
information and tweets are the essential assets for research that can describe the Big Five Personality, including openness,
conscientiousness, extraversion, agreeableness, and neuroticism. Several previous studies have tried the prediction of Big Five
Personality. However, the authors found problems in how to optimize the work of the personality prediction system. So, in this
study, Big Five Personality predictions were carried out on users of Twitter and improved the performance of the personality
prediction system. We implement optimization techniques such as sampling, feature selection, and hyperparameter tuning to
enhance the performance. This study also applies linguistic feature extraction, such as LIWC and TF-IDF. By using 287 Twitter
users that have permitted their data to be crawled acquired from an online survey using Big Five Inventory (BFI), and applying
all optimization techniques, the average accuracy result is 84.22% which is a 74.44% gain over the specified baseline.
Creator
Gita Safitri1
, Erwin Budi Setiawan2
, Erwin Budi Setiawan2
Publisher
Telkom University
Date
27 februari 2022
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Gita Safitri1
, Erwin Budi Setiawan2, “Optimization Prediction of Big Five Personality in Twitter Users,” Repository Horizon University Indonesia, accessed June 1, 2025, https://repository.horizon.ac.id/items/show/9079.