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  1. Relevance Statement Computational personality assessment based on digital footprints and high frequent behavioral data from in-vivo sensing studies could drastically change the concept of personality and its assessment.
  2. Abstract

    To date we know little about natural emotion word repertoires, and whether or how they are associated with emotional functioning. Principles from linguistics suggest that the richness or diversity of individuals’ actively used emotion vocabularies may correspond with their typical emotion experiences. The current investigation measures active emotion vocabularies in participant-generated natural speech and examined their relationships to individual differences in mood, personality, and physical and emotional well-being. Study 1 analyzes stream-of-consciousness essays by 1,567 college students. Study 2 analyzes public blogs written by over 35,000 individuals. The studies yield consistent findings that emotion vocabulary richness corresponds broadly with experience. Larger negative emotion vocabularies correlate with more psychological distress and poorer physical health. Larger positive emotion vocabularies correlate with higher well-being and better physical health. Findings support theories linking language use and development with lived experience and may have future clinical implications pending further research.

  3. From many perspectives, the election of Donald Trump was seen as a departure from long-standing political norms. An analysis of Trump’s word use in the presidential debates and speeches indicated that he was exceptionally informal but at the same time, spoke with a sense of certainty. Indeed, he is lower in analytic thinking and higher in confidence than almost any previous American president. Closer analyses of linguistic trends of presidential language indicate that Trump’s language is consistent with long-term linear trends, demonstrating that he is not as much an outlier as he initially seems. Across multiple corpora from the American presidents, non-US leaders, and legislative bodies spanning decades, there has been a general decline in analytic thinking and a rise in confidence in most political contexts, with the largest and most consistent changes found in the American presidency. The results suggest that certain aspects of the language style of Donald Trump and other recent leaders reflect long-evolving political trends. Implications of the changing nature of popular elections and the role of media are discussed.

  4. Abstract

    Four studies developed and validated two dictionaries to capture agentic and communal expressions in natural language. Their development followed theLinguistic Inquiry and Word Count(LIWC) approach (Study 1) and we tested their validity with frequency‐based analyses and semantic similarity measures. The newly developedAgencyandCommuniondictionaries were aligned withLIWCcategories related to agency and communion (Study 2), and corresponded with subjective ratings (Study 3), confirming their convergent validity. Very low or absent correspondence between proposed dictionaries and unrelatedLIWCcategories demonstrated their discriminant validity (Study 2). Finally, we applied both dictionaries to language used in advertisements. In correspondence to gender stereotypes, male‐dominated jobs were advertised with more agentic than communal words, and female‐dominated jobs with more communal than agentic words (Study 4). Both dictionaries represent reliable tools for quantifying agentic and communal content in natural language, and will improve and facilitate future research on agency and communion.