<![CDATA[The development of Big Data, algorithms, and artificial intelligence (AI) has transformed communication on social media from human-to-human interactions to processes mediated by technological systems. This paper aims to analyze how algorithms shape consumer decisions through digital communication processes and assess the extent to which these decisions can be considered autonomous choices. Using the Model of Interpersonal Communication, this study outlines how algorithms take over communicative functions such as source-receiver, encoding-decoding, message construction, channel selection, and the emergence of noise originating from system limitations. The analysis is deepened through the perspective of Actor-Network Theory, which positions algorithms as non-human actors that mediate and direct the flow of information in digital social networks. The results of the study show that algorithms not only regulate message distribution but also shape preferences, perceptions, and consumption decisions through data-driven personalization, thus making user autonomy relative because choices are made within a decision space curated by the platform's logic. These findings provide theoretical contributions to the development of algorithmic communication studies as well as practical implications for the transparency of recommendation systems and the improvement of digital literacy in the social media era.]]>
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