On Elementary Affective Decisions: To Like Or Not to Like, That Is the Question

Abstract

Perhaps the most ubiquitous and basic affective decision of daily life is deciding whether we like or dislike something/somebody, or, in terms of psychological emotion theories, whether the object/subject has positive or negative valence. Indeed, people constantly make such liking decisions within a glimpse and, importantly, often without expecting any obvious benefit or knowing the exact reasons for their judgment. In this paper, we review research on such elementary affective decisions (EADs) that entail no direct overt reward with a special focus on Neurocognitive Poetics and discuss methods and models for investigating the neuronal and cognitive-affective bases of EADs to verbal materials with differing degrees of complexity. In line with evolutionary and appraisal theories of (aesthetic) emotions and data from recent neurocognitive studies, the results of a decision tree modeling approach simulating EADs to single words suggest that a main driving force behind EADs is the extent to which such high-dimensional stimuli are associated with the “basic” emotions joy/happiness and disgust.

What Is the Difference? Rereading Shakespeare’s Sonnets —An Eye Tracking Study

“…Within the framework of neurocognitive poetics (Jacobs, 2011(Jacobs, , 2015aWillems and Jacobs, 2016;Nicklas and Jacobs, 2017), two steps have been suggested to cope with the innumerable features of texts and/or readers and their many (non-linear) interactions. Firstly, a way should be found to break the complex literary works up into simpler, measurable features, for instance by Quantitative Narrative Analysis (QNA; e.g., Jacobs, 2015aJacobs, , 2017Jacobs, , 2018aJacobs, , 2019Jacobs et al, 2016aKinder, 2017, 2018;. Secondly, proper statistical and machine learning modeling tools should be chosen to cope with intercorrelated, non-linear relationships between the many features which may affect the (re)reading of poetry (e.g., Jakobson and Lévi-Strauss, 1962;Schrott and Jacobs, 2011;Jacobs, 2015aJacobs, ,b,c, 2019Jacobs et al, 2016a,b).…”

Sentiment Analysis for Words and Fiction Characters From the Perspective of Computational (Neuro-)Poetics

“…Following Stone et al's (1966) early content analysis tool, this method uses word lists with rating data like the Berlin Affective Word List (BAWL; Võ et al, 2006Võ et al, , 2009Briesemeister et al, 2011;Jacobs et al, 2015), the Affective Norms for German Sentiment Terms (ANGST; Schmidtke et al, 2014), or the norms by Warriner et al (2013). If one adheres to the theory that valence is a semantic superfeature that results from a yet unknown integration of both experiential and distributional data at least partially represented in associative activation patterns of semantic networks (Andrews et al, 2009;Jacobs et al, 2016a), then SA based on human ratings is the closest to the experiential aspect one can get. Theoretically, the valence value of a given word would thus be computed in the brain from (1) neural activation patterns distributed over the sensory-motor representations of the word's referents (experiential or embodied aspect) and (2) information about the linguistic company the word keeps (e.g., Harris, 1951), as estimated by the size and density of its learned context (distributional aspect).…”

Affective iconic words benefit from additional sound–meaning integration in the left amygdala

“…Thus, an iconic relationship between sound and meaning of words in today's language might be most evident in the affective domain. Our approach in this work is based on an embodied view of language which proposes that meaning is grounded in behavior and neural circuitry of the producer or the interpreter of linguistic signs, and that affective meaning is intertwined with other lexicosemantic aspects (Jacobs, Hofmann, & Kinder, 2016;Meteyard, Cuadrado, Bahrami, & Vigliocco, 2012;Vigliocco et al, 2009, see Aryani, Conrad, et al, 2018, for more explanations). In the present study, we therefore focused on affective iconic words and aimed at extending previous neural evidence on the facilitative role of iconicity in language processing to other classes of words than ideophones, and to the affective domain.…”

“…Notably, the notion of "affective meaning" may not be shared by all theories on linguistic meaning. Our approach in this work is based on an embodied view of language which proposes that meaning is grounded in behavior and neural circuitry of the producer or the interpreter of linguistic signs, and that affective meaning is intertwined with other lexicosemantic aspects (Jacobs, Hofmann, & Kinder, 2016;Meteyard, Cuadrado, Bahrami, & Vigliocco, 2012;Vigliocco et al, 2009, see Aryani, Conrad, et al, 2018, for more explanations).…”