Algorithmic mediations of consumption 85 the algorithms reception, which is a subject little discussed in international scientific journals. We can also see Teixeira Filho (2018) in this discussion, who emphasizes that a good part of the studies on algorithms are demarcated in the debate of their functionalities and applicability or demarcated by the interest in data privacy and the issues of surveillance of the actions of social subjects, considering the ethical implications of such processes. Little has been studied about the effects of algorithms and their appropriation processes in cultures. So, this strong aspect of the social production of algorithmic meaning reinforces what Gillespie (2014) identified as an “algorithmic promise of objectivity,” even if idealized by the intentionality of production, though generalized in uses and consumption since based on the belief that such devices work from the perspective of impartiality, in the sense of what they offer users-consumers as the algorithmic truth. This aspect is false because, in fact, there is a selection of occurrences within commercial interests and what most likely happens, which also favors the commercial aspect of what is offered in the research of data in their programs. Circulation/interaction and reception of the algorithm gain relevance from the perspective of Gillespie (2014) due to the condition of directing (manipulating) the lives of users by performing the mixture that induces [to consume], in the tan- gle of calculations of occurrences, from the use practices of the public-consumers, allowing the design of a predicted or predict- able public. But the question remains: what would be the level of adjustment and accidental in the algorithmic interactions? If there is a probability of occurrence of an event, even if minimal, such an event may occur. This aspect finds its place in the third and fourth stages of this reflection, which consider the sociocultural contexts of the influence of algorithms as narratives and as forms of interactions that predict the most frequent as the principal aspect of manipulation and tends to be generalized, the adjustment resulting from the mixtures of brand and user- consumer interactions by crossing data that favors a revealing dynamics of real and accidental data flows that would demarcate unusual occurrences and, often outside commercial inter-
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