Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Türkiye
Tezin Onay Tarihi: 2019
Tezin Dili: İngilizce
Öğrenci: ESEN TUTAYSALGIR
Asıl Danışman (Eş Danışmanlı Tezler İçin): İsmail Hakkı Toroslu
Eş Danışman: Pınar Karagöz
Özet:In this thesis, we present a framework for predicting the personality traits of users using their tweets written in Turkish. The prediction model is constructed with a clustering based approach. We show how to extract linguistic features from tweet data and to adapt TF-IDF weighting and word embeddings to the Turkish tweets. Since the model is based on linguistic features, it is language specific. The prediction model uses features applicable to Turkish language and related to writing style of Turkish Twitter users. Our approach uses anonymous BIG5 questionnaire scores of volunteer participants as ground truth in order to generate personality model from Twitter posts. Experiment results show that constructed model can predict personality traits of Turkish Twitter users with relatively small errors.