Optimization Prediction of Big Five Personality in Twitter Users
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 neur...
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2022-02-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | http://jurnal.iaii.or.id/index.php/RESTI/article/view/3529 |
| _version_ | 1827364890307723264 |
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| author | Gita Safitri Erwin Budi Setiawan |
| author_facet | Gita Safitri Erwin Budi Setiawan |
| author_sort | Gita Safitri |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-08T08:17:56Z |
| format | Article |
| id | doaj.art-f4f1ce849bc44c36bc3c2224024c5e49 |
| institution | Directory Open Access Journal |
| issn | 2580-0760 |
| language | English |
| last_indexed | 2024-03-08T08:17:56Z |
| publishDate | 2022-02-01 |
| publisher | Ikatan Ahli Informatika Indonesia |
| record_format | Article |
| series | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| spelling | doaj.art-f4f1ce849bc44c36bc3c2224024c5e492024-02-02T06:58:52ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602022-02-0161859110.29207/resti.v6i1.35293529Optimization Prediction of Big Five Personality in Twitter UsersGita Safitri0Erwin Budi Setiawan1Telkom UniversityTelkom UniversityVarious 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.http://jurnal.iaii.or.id/index.php/RESTI/article/view/3529big five personality, svm, tf-idf, liwc, optimization |
| spellingShingle | Gita Safitri Erwin Budi Setiawan Optimization Prediction of Big Five Personality in Twitter Users Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) big five personality, svm, tf-idf, liwc, optimization |
| title | Optimization Prediction of Big Five Personality in Twitter Users |
| title_full | Optimization Prediction of Big Five Personality in Twitter Users |
| title_fullStr | Optimization Prediction of Big Five Personality in Twitter Users |
| title_full_unstemmed | Optimization Prediction of Big Five Personality in Twitter Users |
| title_short | Optimization Prediction of Big Five Personality in Twitter Users |
| title_sort | optimization prediction of big five personality in twitter users |
| topic | big five personality, svm, tf-idf, liwc, optimization |
| url | http://jurnal.iaii.or.id/index.php/RESTI/article/view/3529 |
| work_keys_str_mv | AT gitasafitri optimizationpredictionofbigfivepersonalityintwitterusers AT erwinbudisetiawan optimizationpredictionofbigfivepersonalityintwitterusers |