Impact of Feature Extraction and Feature Selection on Indonesian Personality Trait Classification
| Autor: | Ahmad Fikri Iskandar, Agung Budi Prasetio, Ema Utami |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject Feature extraction Unstructured data Feature selection Personality psychology computer.software_genre language.human_language Indonesian Trait language Personality Social media Artificial intelligence business computer Natural language processing media_common |
| Zdroj: | 2020 3rd International Conference on Information and Communications Technology (ICOIACT). |
| DOI: | 10.1109/icoiact50329.2020.9332107 |
| Popis: | Personality is a characteristic that makes every human being have their individual differences. The ability to measure personality using the conventional approach needed time so long based on the content focuses on the researcher. Twitter is part of a trend social media today that consists of large unstructured data text. The behavior displayed on the contents of tweets by users on Twitter is influenced based on their personalities, making it easier for researchers to make it as data. There are three scenarios done in this work. The best average accuracy is the third scenario is 74.57%, 79.83%, 77.17%, and 66.89%. There is some factor that contributed to increasing performance accuracy, namely, feature extraction, feature selection, and also splitting. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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