Abstract

The increasing amount of data generated from social media brings opportunities to produce various helpful knowledge and information, one of which is predicting a person's personality. The advent of attention-based classification techniques and transformers brings promising results on multiple tasks in Natural Language Processing (NLP). In this study, we predicted the Big Five personalities from Indonesian-language social media by fine-tuning the IndoBERT model. The IndoBERT model is a Bidirectional Encoder Representation from Transformers (BERT)-based mono-language model trained in the Indonesian corpus. Based on the experimental results, the prediction model we proposed obtained an accuracy value of 72% and an F1-score of 71% using IndoBERT-base. Meanwhile, using IndoBERT-large can increase the accuracy value by 78% and the F1-score by 74%. The proposed model also outperforms previous models in predicting the Big Five personality.

Original languageEnglish
Title of host publication2023 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationLeveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages93-98
Number of pages6
ISBN (Electronic)9798350313956
DOIs
Publication statusPublished - 2023
Event24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023 - Hybrid, Surabaya, Indonesia
Duration: 26 Jul 202327 Jul 2023

Publication series

Name2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding

Conference

Conference24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
Country/TerritoryIndonesia
CityHybrid, Surabaya
Period26/07/2327/07/23

Keywords

  • Big Five
  • IndoBERT
  • Indonesian
  • personality prediction
  • social media

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