CROWD-5e: A Croatian psycholinguistic database of affective norms for five discrete emotions

The present study introduces affective norms for a set of 3022 Croatian words on five discrete emotions: happiness, anger, sadness, fear, and disgust. The words were rated by 1239 Croatian native speakers. Each participant rated 251 or 252 words for one discrete emotion on a five-point Likert scale. The analyses revealed a significant relationship between discrete emotions, emotional dimensions (valence and arousal), and other psycholinguistic properties of words. In addition, small sex differences in discrete emotion ratings were found. Finally, the analysis of the distribution of words among discrete emotions allowed a distinction between "pure" words (i.e., those mostly related to a single emotion) and "mixed" words (i.e., those related to more than one emotion). The new database extends the existing Croatian affective norms collected from a dimensional conception of emotions, providing the necessary resource for future experimental investigation in Croatian within the theoretical framework of discrete emotions.

What is the airspeed velocity of an unladen swallow? modeling numerical judgments of realistic stimuli

Research on processes of multiple-cue judgments usually uses artificial stimuli with predefined cue structures, such as artificial bugs with four binary features like back color, belly color, gland size, and spot shape. One reason for using artifical stimuli is that the cognitive models used in this area need known cues and cue values. This limitation makes it difficult to apply the models to research questions with complex naturalistic stimuli with unknown cue structure. In two studies, building on early categorization research, we demonstrate how cues and cue values of complex naturalistic stimuli can be extracted from pairwise similarity ratings with a multidimensional scaling analysis. These extracted cues can then be used in a state-of-the-art hierarchical Bayesian model of numerical judgments. In the first study, we show that predefined cue structures of artificial stimuli are well recovered by an MDS analysis of similarity judgments and that using these MDS-based attributes as cues in a cognitive model of judgment data from an existing experiment leads to the same inferences as when the original cue values were used. In the second study, we use the same procedure to replicate previous findings from multiple-cue judgment literature using complex naturalistic stimuli.

The bright side of words: Norms for 9000 Spanish words in seven discrete positive emotions

In recent years, assumptions about the existence of a single construct of happiness that accounts for all positive emotions have been questioned. Instead, several discrete positive emotions with their own neurobiological and psychological mechanisms have been proposed. Of note, the effects of positive emotions on language processing are not yet properly understood. Here we provide a database for a large set of 9000 Spanish words scored by 3437 participants in the positive emotions of awe, contentment, amusement, excitement, serenity, relief, and pleasure. We also report significant correlations between discrete positive emotions and several affective (e.g., valence, arousal, happiness, negative discrete emotions) and lexico-semantic (e.g., frequency of use, familiarity, concreteness, age of acquisition) characteristics of words. Finally, we analyze differences between words conveying a single emotion ("pure" emotion words) and those denoting more than one emotion ("mixed" emotion words). This study will provide researchers a rich source of information to do research that contributes to expanding the current knowledge on the role of positive emotions in language. The norms are available at https://doi.org/10.6084/m9.figshare.21533571.v2.

Spatio-Temporal Patterns of the SARS-CoV-2 Epidemic in Germany

Results from an explorative study revealing spatio-temporal patterns of the SARS-CoV-2/ COVID-19 epidemic in Germany are presented. We dispense with contestable model assumptions and show the intrinsic spatio-temporal patterns of the epidemic dynamics. The analysis is based on COVID-19 incidence data, which are age-stratified and spatially resolved at the county level, provided by the Federal Government's Public Health Institute of Germany (RKI) for public use. Although the 400 county-related incidence time series shows enormous heterogeneity, both with respect to temporal features as well as spatial distributions, the counties' incidence curves organise into well-distinguished clusters that coincide with East and West Germany. The analysis is based on dimensionality reduction, multidimensional scaling, network analysis, and diversity measures. Dynamical changes are captured by means of difference-in-difference methods, which are related to fold changes of the effective reproduction numbers. The age-related dynamical patterns suggest a considerably stronger impact of children, adolescents and seniors on the epidemic activity than previously expected. Besides these concrete interpretations, the work mainly aims at providing an atlas for spatio-temporal patterns of the epidemic, which serves as a basis to be further explored with the expertise of different disciplines, particularly sociology and policy makers. The study should also be understood as a methodological contribution to getting a handle on the unusual complexity of the COVID-19 pandemic.

Tracing the evolution of personality cognition in early human civilisations: A computational analysis of the Gilgamesh epic

Assessing evolution of cognitive structures across historical periods has remained challenging in the absence of direct access to humans from the past. Overcoming some of these challenges, we examined shifts in the implicit cognitive structures in the Epic of Gilgamesh, which is one of the earliest surviving pieces of literature, circulating in various versions over a period of approx. 2000 years in ancient Mesopotamia. Using a canonical English translation, we applied natural language processing (NLP) and human coding to extract low-dimensional representations of the implicit personality structure in three different historical epochs. We found systematic shifts over time with increasing complexity and increasing resemblance of contemporary personality models in later periods. We discuss how lexical analyses of ancient texts using trait co-occurrence analyses can provide novel insights on the evolution of human behaviour of relevance for contemporary social and behavioural science and the study of ancient societies.