Tables 2 to 4 above show that eye movement was commented on more often than head or hand, which in turn suggests that there was a lot of eye contact between the actors – as was generally expected from active interaction. This suggestion is also supported by the large number of nods as well as blinks, which usually accompany conversational events. Most of the time, speakers kept their hands flat and again alluded to the non-confrontational nature of the dialogues; while the predominant use of the right hand against the left hand speaks of the predominant righteousness of the actors. Questions such as “What do you think?” also help the other person feel open to a discussion and care about their opinion. Subject (Casarrubea et al., 2015, 2018; Magnusson et al., 2016; patternvision.com) seems to grasp the optionality of possible model-forming events, overcome the strict requirement of contiguity of certain analyses, and overcome the limitation of predetermined intervals between events, as implied by time series analysis. As such, it captures the inherent property of behavioral patterns of variability (between the subject and within the subject) in both composition and timing, and defines the appearance of models by statistical probabilities. The theme is a statistical environment that calculates all these conditions and determines which of the theoretically possible co-occurrences or sequences of any two events gives a minimal (i.e. first-level) model. The calculation by theme is based on the concept of the critical interval: it determines which of the temporal occurrences of two events such as A and B are in an interval that meets the condition of a certain probability, e.B.
p = 0.005. The subject recursively maps two events to a minimal model or minimal models to more complex models, thus constructing a theoretically unfinished hierarchy of events and models. The theme has another important concept: while intuitively connecting an event to its duration, the theme considers both the starting and ending points of such an event as a separate event and individually associates them with each other to form a model. In this way, Theme can grasp the difference between the following two situations: in the first, B begins to answer A`s question while A still speaks, in the second, B begins to answer only after A has finished the question. The fact that the theme is fundamentally based on discrete points in time associated with any type of events allows us to try to discover even patterns of behavior hidden from the naked eye, that is, without relying on stereotypes. However, the only limitation of Theme is understandable: it can only identify patterns based on events that have already been commented. Theoretically, the responsibility for selecting the categories to comment on (classes in terms of theme) lies solely in the design of the annotation scheme. However, our work is also limited by the computing power currently available: in order to successfully handle a reasonable number of calculations, our search for models was limited to the annotation classes listed in the previous section. However, we hope that the resulting patterns will prove to be representative of the agreement and match our daily intuitions. This is what the next section is supposed to offer. I want to learn to speak English by communicating with someone via Skype I have perfected writing and reading I want to be a conversation with anyone who speaks in English Okay and not in a simple binary relationship: there can be several nuances, degrees of this behavior (complete or partial), indecision about the opinion to respect or defend (uncertainty), or even a total absence of it (indifference). Recognizing these approval/rejection variants is a key factor in mediating a successful conversation: not recognizing or misinterpreting match events can even lead to the total failure of the given interaction.
Although languages generally have a number of lexical and syntactic means to express this behavior, it can still be misleading to rely solely on linguistic form. For example, if actor B agrees with actor A, he will say “yes”; However, the same “yes” can also be used to suggest exactly the opposite, that is, to signify disagreements – depending on how the “yes” is pronounced. Alternatively, one can agree or disagree by not even saying a word, just by remaining silent: again, it is the non-verbal behavior that contributes to the understanding of the context, effectively to the pragmatic interpretation of the event. Therefore, in order to correctly identify cases of pragmatic functions of agreement/disagreement, it is necessary to take into account all available modalities, verbal and non-verbal, audio or visual. However, there is another challenge here. When a person expresses consent by saying “yes” and nodding at the same time, this agreement is identified as the simultaneous occurrence, the virtual temporal orientation of both events (verbal and gestural). But how can we justify the wisdom of the proverb “silence gives consent”, that is, how to interpret agreement on the basis of the absence of the simultaneous occurrence of behavioral events? In fact, it`s not like we`re facing zero entries here. .
