OTİZME YÖNELİK TÜRKÇE TWİTTER İLETİLERİNİN YAPAY ZEKÂ TEMELLİ DUYGU ÇÖZÜMLEMESİ

Bu çalışmada 29 Mayıs 2023 ila 2 Haziran 2023 tarihleri arasında otizme yönelik Türkçe Twitter iletilerinin yapay zekâ uygulamaları marifetiyle duygu çözümlemesinin yapılması amaçlanmıştır. Mevcut çalışmada yapay zekâ uygulamalarından biri olan Python Tweepy uygulaması ile otizm ile ilgili Türkçe Twitter iletileri incelendi ve söz konusu bu iletilerin duygu çözümlemesi yapıldı. İletilerin taranmasında “otizm” anahtar kelime olarak kullanılmıştır. Transformatörlerden Çift Yönlü Kodlayıcı Beyanı (Bidirectional Encoder Representations from Transformers-BERT) yöntemi ile özellik çıkarımı yapılarak yapay sinir ağları ile iletiler olumlu ve olumsuz olarak iki kutupta sınıflandırıldı. Bu çalışmada otizme dair yayınlanan Twitter iletilerinden rasgele 1000 tanesi seçildi. Buna göre otizm ile ilgili paylaşılan iletilerin %66’sında olumlu, %34’ünde ise olumsuz duygular içerdiği belirlendi. Bu çalışmada yapay zekâ temelli duygu çözümlemesiyle incelenen ve otizmle ile ilgili Türkçe iletilerin sıklıkla olumlu duygular içerdiği belirlendi. Bu iletiler genellikle otizm farkındalığına yönelik basit cümle içerikleri veya mesleki dernekler ve ruh sağlığı çalışanları tarafından toplumu bilgilendirmek amacıyla yazılmıştır.

Anahtar Kelimeler:

Psikoloji, Otizm, Sosyal Medya, Twitter, Doğal Dil İşleme

ARTIFICIAL INTELLIGENCE-BASED SENTIMENT ANALYSIS of TURKISH TWEETS RELATED to AUTISM

In this study, it was aimed to conduct sentiment analysis of Turkish Twitter messages about autism between May 29, 2023 and June 2, 2023 through artificial intelligence applications. In the current study Turkish tweets related to autism were examined with the Python Tweepy application, which is one of the artificial intelligence applications, and the sentiment analysis of these tweets was performed. “Autism” is used as a keyword for scanning the tweets. By using the Bidirectional Encoder Representations from Transformers (BERT) method from transformers, feature extraction was performed, and the tweets were classified as positive and negative in two polarities with artificial neural networks. 1000 of the tweets about autism were randomly selected. Accordingly, it was determined that 66% of the tweets about autism contained positive and 34% of negative emotions. In this study, it was determined that Turkish tweets about autism, which were analyzed with artificial intelligence-based emotion analysis, often contained positive emotions. These messages are typically written by professional associations and mental health workers with the aim of raising awareness about autism, using simple sentence content targeting autism awareness.

Keywords:

Psychology, Autism, Social Media, Twitter, Natural Language Processing,

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