Constructing Semantic Models From Words,Images, and Emojis

A number of recent models of semantics combine linguistic information, derived from text corpora, and visual information, derived from image collections, demonstrating that the resulting multimodal models are better than either of their unimodal counterparts, in accounting for behavioral data. Empirical work on semantic processing has shown that emotion also plays an important role especially in abstract concepts; however, models integrating emotion along with linguistic and visual information are lacking. Here, we first improve on visual and affective representations, derived from state-of-the-art existing models, by choosing models that best fit available human semantic data and extending the number of concepts they cover. Crucially then, we assess whether adding affective representations (obtained from a neural network model designed to predict emojis from co-occurring text) improves the model's ability to fit semantic similarity/relatedness judgments from a purely linguistic and linguistic–visual model. We find that, given specific weights assigned to the models, adding both visual and affective representations improves performance, with visual representations providing an improvement especially for more concrete words, and affective representations improving especially the fit for more abstract words.     

Making Sense of the Hands and Mouth: The Role of “Secondary” Cues to Meaning in British Sign Language and English

Successful face-to-face communication involves multiple channels, notably hand gestures in addition to speech for spoken language, and mouth patterns in addition to manual signs for sign language. In four experiments, we assess the extent to which comprehenders of British Sign Language (BSL) and English rely, respectively, on cues from the hands and the mouth in accessing meaning. We created congruent and incongruent combinations of BSL manual signs and mouthings and English speech and gesture by video manipulation and asked participants to carry out a picture-matching task. When participants were instructed to pay attention only to the primary channel, incongruent “secondary” cues still affected performance, showing that these are reliably used for comprehension. When both cues were relevant, the languages diverged: Hand gestures continued to be used in English, but mouth movements did not in BSL. Moreover, non-fluent speakers and signers varied in the use of these cues: Gestures were found to be more important for non-native than native speakers; mouth movements were found to be less important for non-fluent signers. We discuss the results in terms of the information provided by different communicative channels, which combine to provide meaningful information.     

Investigating the Relationships Between Mobility Behaviours and Indicators of Subjective Well-Being Using Smartphone-Based Experience Sampling and GPS Tracking

People interact with their physical environments every day by visiting different places and moving between them. Such mobility behaviours likely influence and are influenced by people's subjective well-being. However, past research examining the links between mobility behaviours and well-being has been inconclusive. Here, we provide a comprehensive investigation of these relationships by examining individual differences in two types of mobility behaviours (movement patterns and places visited) and their relationship to six indicators of subjective well-being (depression, loneliness, anxiety, stress, affect, and energy) at two different temporal levels of analysis (two-week tendencies and daily level). Using data from a large smartphone-based longitudinal study (N = 1765), we show that (i) movement patterns assessed via GPS data (distance travelled, entropy, and irregularity) and (ii) places visited assessed via experience sampling reports (home, work, and social places) are associated with subjective well-being at the between and within person levels. Our findings suggest that distance travelled is related to anxiety, affect, and stress, irregularity is related to depression and loneliness, and spending time in social places is negatively associated with loneliness. We discuss the implications of our work and highlight directions for future research on the generalizability to other populations as well as the characteristics of places. © 2020 European Association of Personality Psychology     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.     

Complex mediating effects of rumination facets between personality traits and depressive symptoms

This study investigates whether facets of rumination statistically mediate the relationships between Big Five personality traits and depressive symptoms. Self-reported personality traits and rumination were investigated as predictors of depressive symptoms in a cross-sectional sample of 3043 participants aged 18–60 years (68.8% female). Multiple regression analysis investigated which personality traits and rumination facets best explained variance in depressive symptoms. Structural equation modelling was used to determine whether facets of rumination mediated the relationships between personality traits and depressive symptoms. Multiple regression analysis found that variance in depressive symptoms was best explained by the personality traits neuroticism, extroversion, conscientiousness; and both facets of rumination, brooding and reflection. Structural equation modelling added that the effects of neuroticism, extroversion, conscientiousness and openness on depressive symptoms were statistically mediated by brooding; the effects of neuroticism, extroversion and openness to depressive symptoms were statistically mediated by reflection. Rumination facets statistically mediated the effects of various personality traits on depressive symptoms. These results provide insights into which individuals may be best suited to treatments for depression targeting rumination.     

Belief merging and the discursive dilemma: an argument-based account to paradoxes of judgment aggregation

The aggregation of individual judgments on logically interconnected propositions into a collective decision on the same propositions is called judgment aggregation. Literature in social choice and political theory has claimed that judgment aggregation raises serious concerns. For example, consider a set of premises and a conclusion where the latter is logically equivalent to the former. When majority voting is applied to some propositions (the premises) it may give a different outcome than majority voting applied to another set of propositions (the conclusion). This problem is known as the discursive dilemma (or paradox). The discursive dilemma is a serious problem since it is not clear whether a collective outcome exists in these cases, and if it does, what it is like. Moreover, the two suggested escape-routes from the paradox—the so-called premise-based procedure and the conclusion-based procedure—are not, as I will show, satisfactory methods for group decision-making. In this paper I introduce a new aggregation procedure inspired by an operator defined in artificial intelligence in order to merge belief bases. The result is that we do not need to worry about paradoxical outcomes, since these arise only when inconsistent collective judgments are not ruled out from the set of possible solutions.     

Philosophy of science in Hungary

The report gives a survey of the Hungarian philosophy of science after 1973. The report throws some light on the history of Hungarian philosophy in the context of the political circumstances of the late sixties and seventies. It starts with the not so well-known history of persecution of philosophers in 1973. Then it treats the emergence of the philosophy of science focussing on the most significant representatives of this branch of philosophy, which was up to that time almost unknown in Hungary. Due to the fact that the important results in Hungarian philosophy of science run parallel with the reception and translation of the significant products of Western philosophy, such as Wittgenstein's, Popper's, Kuhn's, or Polanyi's works, the report gives relatively significant room to treat these achievements. The last part of the report presents a survey of the younger generation of the philosophers of science, concentrating on the most important insights.It is the sad duty of the editor to inform readers that Dr. Gabriella Ujlaki died shortly after finishing this Report.     

Video-based assessment of interpersonal problem solving skills in patients with schizophrenia, their siblings and non-psychiatric controls

The aim of this study was to analyze social functioning in patients with schizophrenia and their biological relatives with a Swedish version of the video-based vignette test Assessment of Interpersonal Problem Solving Skills (AIPSS). In a new video production with simulated "real life" situations we tested the ability to receive, process and send social information in 25 individuals with a DSM-IV diagnosis of schizophrenia, 20 siblings to patients with schizophrenia and 25 randomly selected non-psychiatric controls. The test proved to have good validity and interrater reliability. After controlling for positive or negative symptoms, patients had poor performance especially in acting out solutions leading to effective problem solving. Siblings generally did not differ from controls, but showed some deficiencies in non-verbal language. To conclude, AIPSS is appropriate for use in a Swedish-speaking context and might be useful in research on vulnerability indicators and in assessment of treatment interventions.