Empathy is an important human ability associated with successful social interaction. It is currently unclear how to optimally measure individual differences in empathic processing. Although the Big Five model of personality is an effective model to explain individual differences in human experience and behavior, its relation to measures of empathy is currently not well understood. Therefore, the present study was designed to investigate the relationship between the Big Five personality concept and two commonly used measures for empathy (Empathy Quotient (EQ), (...) Interpersonal Reactivity Index (IRI)) in four samples from China, Germany, Spain and the United States of America. This approach was designed to advance the way the Big Five personality model can be used to measure empathy. We found evidence of medium effect sizes for associations between personality and empathy, with agreeableness and conscientiousness as the most important predictors of affective and cognitive empathy (measured by the respective IRI subscales) as well as a for a one-dimensional empathy score (measured by the EQ). Empathy in a fictional context was most closely related to openness to experience while personal distress was first of all related to neuroticism. In terms of culture, we did not observe any distinct pattern concerning cultural differences. These results support the cross-cultural applicability of the Empathy Quotient and the Interpersonal Reactivity Index and indicate structurally similar associations between personality and empathy across cultures. (shrink)

We present a study of the linguistic output of the German-speaking writer Robert Walser using Natural Language Processing (NLP). We curated a corpus comprising texts written by Walser during periods of sound health, and writings from the year before his hospitalization, and writings from the first year of his stay in a psychiatric clinic, all likely attributed to schizophrenia. Within this corpus, we identified and analyzed a total of 20 linguistic markers encompassing established metrics for lexical diversity, semantic similarity, and (...) syntactic complexity. Additionally, we explored lesser-known markers such as lexical innovation, concreteness, and imageability. Notably, we introduced two additional markers for phonological similarity for the first time within this context. Our findings reveal significant temporal dynamics in these markers closely associated with Walser’s contemporaneous diagnosis of schizophrenia. Furthermore, we investigated the relationship between these markers, leveraging them for classification of the schizophrenic episode. (shrink)

Artificial intelligence represents a key technology being inbuilt into evermore products. Research investigating attitudes towards artificial intelligence surprisingly is still scarce, although it becomes apparent that artificial intelligence will shape societies around the globe. To better understand individual differences in attitudes towards artificial intelligence, the present study investigated in n = 351 participants associations between the Affective Neuroscience Personality Scales (ANPS) and the Attitudes towards Artificial Intelligence framework (ATAI). It could be observed that in particular higher levels of SADNESS were (...) associated with higher negative attitudes towards AI (fearing AI). The findings are discussed in this work from an evolutionary perspective because primary emotional systems—according to Affective Neuroscience Theory—represent tools for survival, which have been homologously conserved across mammalian species including homo sapiens. (shrink)

Given recent advances in technology, connectivity, and the popularity of social media platforms, recent literature has devoted great attention to problematic Facebook use. However, exploring the potential predictors of problematic social media use beyond Facebook use has become paramount given the increasing popularity of multiple alternative platforms. In this study, a sample of 584 social media users was recruited to complete an online survey assessing sociodemographic characteristics, patterns, and preferences of social media use, problematic social media use, social media use (...) motives, psychological well-being, self-esteem, and positive and negative affect. Results indicated that 6.68% of all respondents could be potentially classed as problematic users. Moreover, further analysis indicated that intrapersonal motive, negative affect, daily social media use, surveillance motive, and positive affect each predicted PSMU. These variables accounted for about 37% of the total variance in PSMU, with intrapersonal motive driving the greatest predictive contribution, over and above the effects of patterns of social media use and sociodemographic variables. These findings contribute to the increasing literature on PSMU. The results of this study are discussed in light of the existing literature on PSMU. (shrink)

In the age of surveillance capitalism, the prevailing business model underlying the use of social media applications (“apps”) foresees the exchange of personal data for the allowance to use an online service. Such a data business model comes with many potential negative side effects ranging from violation of privacy issues to election manipulation. Therefore, it is of utmost importance to think of alternatives to the current data business model. The present study investigated how strong the support would be for a (...) monetary payment model among a sample of 210 participants. Participants were asked about their willingness to pay for social media, if in turn their data would be private and other problems concerning social media use would be tackled. Only one-fifth of participants (21.43%) supported such a model. From the Big Five Personality traits, Agreeableness was positively associated with support of such a model. Finally, data are also provided on how much participants would be willing to pay for social media on a monthly basis. The present study’s findings are of a preliminary nature and will contribute to the start of an important discussion. (shrink)

More than three billion users are currently on one of Meta’s online platforms with Facebook being still their most prominent social media service. It is well known that Facebook has designed a highly immersive social media service with the aim to prolong online time of its users, as this results in more digital footprints to be studied and monetized. In this context, it is debated if social media platforms can elicit addictive behaviors. In the present work, we demonstrate in N (...) = 1,094 users that it is possible to predict from digital footprints of the Facebook users their self-reported addictive tendencies toward social media by applying machine-learning strategies. More specifically, we analyzed the predictive power of a set of models based on different sets of features extracted from digital traces, namely posting activity, language use, and page Likes. To maximize the predictive power of the models, we used an ensemble of linear and non-linear prediction algorithms. This work showed also sufficient accuracy rates in distinguishing between disordered and non-disordered social media users. In sum, individual differences in tendencies toward “social networks use disorder” can be inferred from digital traces left on the social media platform Facebook. Please note that the present work is limited by its cross-sectional design. (shrink)

Pain perception is influenced by several factors, and among them, affect, sex, and perception of bodily signals are assumed to play a prominent role. The aim of the present study is to explore how sex, cardiac interoceptive accuracy, and the interaction of the latter two influence the perception of experimentally induced pain. We investigated a large sample of young adults, assessing current positive and negative affective state with the Positive and Negative Affect Schedule, cardiac interoceptive accuracy with the mental heartbeat (...) tracking task, and pain sensitivity with electrical stimulation on the back of the dominant hand, applying a repeated-measures staircase protocol. Males showed a significantly higher pain threshold and tolerance level than females, whereas cardiac interoceptive accuracy was not associated with pain sensitivity. The impact of sex × cardiac interoceptive accuracy interaction was significant for pain threshold only, while pain tolerance was predicted only by sex. According to these findings, the associations between pain sensitivity, cardiac IAc, and sex might be more complicated than it was supposed in previous studies. Interactions between factors impacting pain perception appear worthy of further investigation. (shrink)