From Data to Emotion: A Multimodal Approach to Real-Time EmotionAware Marketing
8th International Conference on Technology, Engineering and Science, IConTES 2025, Antalya, Türkiye, 12 - 15 Kasım 2025, cilt.38, ss.538-550, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası: 38
- Doi Numarası: 10.55549/epstem.1251
- Basıldığı Şehir: Antalya
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.538-550
- Anahtar Kelimeler: Apache flink, Apache kafka, Personalized marketing, Real-time recommendation, Stream processing
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Boğaziçi Üniversitesi Adresli: Evet
Özet
This study presents a system that aims to dynamically analyze users' emotional states and deliver real-time campaign recommendations. Recognizing that emotional cues manifest across different channels, the system adopts a multimodal approach that integrates biometric signals, social media content (both visual and textual), and application behavior data. By fusing these diverse data sources, the system enhances its ability to accurately infer users' emotional states. Data is collected from mobile applications, wearable devices, and thirdparty platforms. Apache Kafka serves as the message broker, while Apache Flink performs real-time event processing—either directly or after interpretation by the Artificial Intelligence Module. Campaigns are selected based on the inferred emotional state and pushed to the user as personalized recommendations. The high-level goal of this work is to develop a robust multimodal AI model capable of detecting users' emotional states from heterogeneous data streams. Unlike existing approaches, this system integrates multimodal signals in real time, and it is expected to achieve high accuracy in emotion recognition. This system has strong potential for deployment in smart services, user engagement platforms, and real-time decision-making environments.