Yazar "Cakar, T." seçeneğine göre listele

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    Analyzing Consumer Behavior: The Impact of Retro Music in Advertisements on a Chocolate Brand and Consumer Engagement
    (Institute of Electrical and Electronics Engineers Inc., 2023) Filiz, G.; Cakar, T.; Soyaltin, T.E.; Girisken, Y.; Turkyilmaz, C.A.
    This study presents research utilizing binary classification models to analyze consumer behaviors such as chocolate consumption and retro music ad viewing. Retro music, with its potential to evoke nostalgic feelings in consumers, is used in advertisements, which can have a significant impact on brand perception and consumer engagement. Firstly, a model focusing on chocolate consumption was developed and tested. The model yields significant outcomes. Secondly, a model based on retro music ad viewing status was developed and tested. Significant potential findings were obtained. This study emphasizes the applicability of effective classification models that can be used to understand and predict consumer behaviors, yielding significant outcomes. © 2023 IEEE.
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    Liking Prediction Using fNIRS and Machine Learning: Comparison of Feature Extraction Methods
    (Institute of Electrical and Electronics Engineers Inc., 2022) Koksal, M.Y.; Cakar, T.; Tuna, E.; Girisken, Y.
    The fMRI method, which is generally used to detect behavioral patterns, draws attention with its expensive and impractical features. On the other hand, near infrared spectroscopy (fNIRS) method is less expensive and portable, but it is as effective as fMRI in creating a good prediction model. With this method, a model has been developed that can predict whether people like a stimulus or not, using machine learning various algorithms. A comparison was made between feature extraction methods, which was the main focus while developing the model. © 2022 IEEE.