Written narratives can provide insight into the mental and affective state of a person. However, current methods of analysis require extensive manual human coding, limiting the sample size that can feasibly be analyzed. Computational approaches using natural language processing offer promise as a rapid means of examining characteristics of narrative texts. Though used extensively in social media and customer reviews in industry, their classification accuracy relative to human coders remains unclear for psychological data. We compared the congruence of two popular lexicon-based sentiment analysis tools, Valence Aware Dictionary and sEntiment Reasoner (VADER) and TextBlob, with self-reported valence, for 3,309 narratives representing autobiographical memories from two different data sets. Both tools, but especially TextBlob, displayed a bias in rating memories as neutral in valence. Across both data sets, VADER consistently produced more congruent classifications than did TextBlob. Accuracy improved significantly, to moderate levels of congruence (rMCC = .32), on par with that of human coders reported in other work, when classification was limited to three valence types (negative, neutral, or positive) rather than five. Tool performance remained consistent regardless of data set size. VADER, more so than TextBlob, is a useful means of rapidly determining the broad emotional valence within large volumes of text data that would be unfeasible for manual coding. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Several parameters can influence children's enumeration processes, including the numerosity and configuration of the elements. Few studies have examined young children's enumeration from a developmental perspective, especially using eye-tracking data, highlighting the novelty of the present study. Eye movements analysis can indeed give crucial information to understand in depth the construction of enumeration processes in childhood. In this study, we analyzed how kindergarten pupils enumerated elements displayed on a computer screen and how far their responses were influenced by their age and three other parameters, namely, the numerosity, configuration, and colour of the elements. Behavioural measures were combined with eye tracking to gain detailed insights into visual attention patterns during enumeration tasks. Results revealed a strong effect of configuration on enumeration. Errors were more frequent and response times longer with random arrangements versus dice configurations. Five-year-olds performed better on enumeration tasks than 4-year-olds when the elements were in random arrangements and in the counting range. Eye-tracking data confirmed behavioural results and revealed additionally that visual attention was more uniformly distributed across all the dots and associated with longer scanpaths when these dots were displayed in random arrangements versus dice configurations. These findings suggest that structured configurations may reduce cognitive load by supporting pattern recognition, thereby improving children's efficiency in enumeration tasks. Our results support the assumption that pattern recognition plays a fundamental role in the acquisition of enumeration abilities and that young children use qualitatively different enumeration processes for small numerosities depending on the configuration of the elements. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
The number of available response options is a central design feature in any experimental psychology paradigm, with binary response paradigms restricting the range of behavioural responses into staying or shifting. Participants (n = 72) played nine blocks of a novel zero-sum game, Dice Dual, while we parametrically manipulated the different number of response options (2, 4, 6) against an unexploitable computerized opponent. When the number of responses exceeded two, this allowed us to identify two types of shift behaviours: between-category shifts relevant to mental model exploitation and within-category shifts reflective of random exploration. Between-category shifts were sensitive to outcome valence, exhibiting an increased shift rate when more response options were available after win, while shift rates were independent of response availability after loss. In contrast, within-category shifts were only sensitive to response availability, with increased shift rates when more response options were available, irrespective of outcome valence. Identifying multiple, functionally different classes of shift behaviour using nonbinary response paradigms allows us to more easily separate attempts at exploitation and exploration. The data also offer more general models of performance regarding suboptimal decision making, where negative outcomes constrict the range of factors considered in future mental model updates.
It is generally well known that emotion can benefit memory; however, much less is known about how emotion influences metamemory. The present study examined how list composition and emotion influence individuals' metamnemonic judgements and performance in a free recall task. Participants studied lists of words that varied in emotional valence and made immediate judgements of learning after each word. Valence was manipulated in a mixed-list design in Experiment 1, a pure-list design in Experiment 2, and in a mixed- versus pure-list design in Experiment 4; arousal was held constant. We expected that the relative influence of emotion on metamemory would depend on participants' beliefs about how emotion influences memory and that these beliefs would be more salient in a mixed-list than pure-list design. Consistent with this, emotional words were given higher judgements of learnings than neutral words in Experiments 1 and 4, but not in Experiment 2. Posttest questionnaires (Experiments 1 and 2) and data collected from a naïve participant sample (Experiment 3) indicated that participants believed that emotional words are more memorable than nonemotional words. These results suggest that list structure influenced the degree to which judgements of learnings were responsive to emotional content. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Research on smile perception indicates that smiles containing a cheek raiser tend to be judged as happier, more sincere, and more authentic than those without this cue. However, while this is well established for human smiles, less is known about how such cues are perceived in emojis. Guided by the emotions as social information (EASI) model, which posits that emotional expressions influence observers through inferential and affective pathways, this study examined judgements of sincerity for enjoyment and nonenjoyment smiles produced by human and emoji encoders. In Experiment 1, participants judged whether smiles (human or emoji) were "really happy" or "not really happy." Both stimulus types included smiles that varied in cues of sincerity (presence or absence of the cheek raiser). In Experiment 2, the same task was repeated with open or closed mouth variations. Participants identified human enjoyment smiles as "really happy" more often than nonenjoyment smiles, whereas emojis were rated as "really happy" regardless of the sincerity cue. Closed mouth smiles were judged as less happy than open mouth smiles, and judgements were faster for emojis than for human faces. These findings suggest that, in line with the EASI model, emoji-based expressions may elicit affective rather than inferential processing, highlighting their limited equivalence to human smiles in digital communication. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
