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Clustering based personality prediction on turkish tweets
Date
2019-08-30
Author
Tutaysalgir, Esen
Karagöz, Pınar
Toroslu, İsmail Hakkı
Metadata
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In this paper, we present a framework for predicting the personality traits by analyzing tweets written in Turkish. The prediction model is constructed with a clustering based approach. 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 BIGS questionnaire scores of volunteer participants as the 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.
Subject Keywords
Personality analysis
,
Twitter
,
Clustering
,
Text mining
URI
https://hdl.handle.net/11511/37038
DOI
https://doi.org/10.1145/3341161.3343513
Conference Name
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Collections
Department of Computer Engineering, Conference / Seminar
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E. Tutaysalgir, P. Karagöz, and İ. H. Toroslu, “Clustering based personality prediction on turkish tweets,” presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Vancouver, Canada, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37038.