Depression Detection on Twitter Social Media Platform using Bidirectional Long-Short Term Memory

ANDRE AGASI SIMANUNGKALIT

Informasi Dasar

106 kali
23.04.2499
302.23
Karya Ilmiah - Skripsi (S1) - Reference

Depression is one of the mental disorders that are often experienced by a person in daily life. Social media platforms is a new thing as an alternative to tell stories and express current feelings by people today. Twitter is one of the social media that is often used to express feelings and opinions through tweets posts, including tweets that contain hate speech which indirectly shows symptoms of depressive disorder through statements uploaded. It also requires modeling that can recognize users with the potential to experience depression so that they can get initial treatment. This can be implemented using the BiLSTM (Bidirectional Long Short-Term Memory) method and the Word2Vec feature. It is also needs a modeling that can recognize the users who have the potential to experience depression so that they can get treatment at the beginning. This can be implemented using the BiLSTM (Bidirectional Long Short-Term Memory) method and the Word2Vec feature.

Subjek

Natural language processing
SOCIAL MEDIA-POLITICAL ASPECTS,

Katalog

Depression Detection on Twitter Social Media Platform using Bidirectional Long-Short Term Memory
 
 
Indonesia

Sirkulasi

Rp. 0
Rp. 0
Tidak

Pengarang

ANDRE AGASI SIMANUNGKALIT
Perorangan
Warih Maharani, Prati Hutari Gani
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2023

Koleksi

Kompetensi

  • CII4E4 - TUGAS AKHIR

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