Emotional Reactivity Classification Using Artificial Intelligence Based on Twitter in Bahasa Indonesia

Twitter is one of Indonesia's most widely used social media to express positive and negative emotions. Negative emotions are referred to as emotional reactivity, an example of which is depression. To detect emotional reactivity, Artificial Intelligence (AI) was used. With deep learning pretrain...

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Veröffentlicht in:2023 IEEE 3rd International Conference on Social Sciences and Intelligence Management (SSIM) S. 144 - 148
Hauptverfasser: Paramita, Greta V., Andangsari, Esther W., Kemala, Ade P., Ali, Moondore M., Putri, Trisa M., Puspita, Katarina I.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 15.12.2023
Schlagworte:
Analytical models
artificial intelligence
Blogs
Deep learning
Depression
emotional reactivity
Social networking (online)
Social sciences
Training
twitter
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Zusammenfassung:Twitter is one of Indonesia's most widely used social media to express positive and negative emotions. Negative emotions are referred to as emotional reactivity, an example of which is depression. To detect emotional reactivity, Artificial Intelligence (AI) was used. With deep learning pretrained model methods (IndoBERT and IndoBERTweet), AI successfully classified emotional reactivity. AI satisfactorily detected emotional reactivity on Twitter.
DOI:10.1109/SSIM59263.2023.10468872