Probability And Bayesian Inference In Human Communication - Pavel Slutskiy (WACANA: Jurnal Ilmiah Ilmu Komunikasi, 2024)
This paper challenges the applicability of traditional information theory's frequentist approach to human communication, arguing that it fails to capture the unique, singular nature of communicative acts. Traditional theory, based on long-term observation and relative frequencies, overlooks the complexity and context-dependency inherent in human interactions. The objective is to redefine communication understanding through a Bayesian model that emphasises subjective probability and the critical role of beliefs and intentions. Utilising a rationalist methodology, the research conducts a qualitative analysis of theoretical concepts and prior research, proposing a new model that situates probability within the philosophy of communication. This model highlights the subjective beliefs and intentions that govern communication, challenging existing paradigms and contributing to a deeper understanding of communicative dynamics. The results reveal the limitations of the frequentist approach and demonstrate the applicability of a Bayesian perspective, advocating for a paradigm shift in communication theory towards a sender-oriented model. This shift not only challenges existing paradigms but also offers a more nuanced understanding of communication as a fundamentally human endeavour.