The effect of temperature on language complexity: Evidence from seven million parliamentary speeches

Climate change carries important effects on human wellbeing and performance, and increasingly research is documenting the negative impacts of out-of-comfort temperatures on workplace performance. In this study, we investigate the plausibly causal effect of extreme temperatures, i.e., out-of-comfort, on language complexity among politicians, leveraging a fixed effects strategy. We analyze language complexity in over seven million parliamentary speeches across eight countries, connecting them with precise daily meteorological information. We find hot days reduce politicians' language complexity, but not cold days. Focusing on one country, we explore marginal effects by age and gender, suggesting high temperatures significantly impact older politicians at lower thresholds. The findings propose that political rhetoric is not only driven by political circumstances and strategic concerns but also by physiological responses to external environmental factors. Overall, the study holds important implications on how climate change could affect human cognitive performance and the quality of political discourse.

Marital quality improves self- and partner-reported psychopathy among Chinese couples: A longitudinal study

BACKGROUND

Psychopathy is closely related to many negative interpersonal outcomes in daily life, including violence. Therefore, psychopathy intervention in subclinical individuals has significant application value.

OBJECTIVE

Guided by the personality-relationship transaction model and social investment theory, this study examined how marital quality affects self- and partner-rated psychopathy. We also used the actor-partner interdependence mediation model to explore the mediating effect of communication.

METHODS

We examined self-reports and partner reports of psychopathy, marital quality, and communication among 260 married Chinese couples.

RESULTS

The results indicated that marital quality directly influenced couples' self-rated psychopathy, with both actor and partner effects on husbands' psychopathy and actor effects on wives' psychopathy. Moreover, verbal communication had mediating effects at time 2 between marital quality at time 1 and partner-reported psychopathy at time 3. Meanwhile, the mediating effect of nonverbal communication was not significant.

CONCLUSION

Our investigation of relationship effects on psychopathy revealed that the underlying mechanisms differed between self- and partner-rated psychopathy. The findings can highlight directions for exploring potential intervention strategies for subclinical psychopathy.

A systematic literature review on SME internationalization: a personality lens

The importance of the individual decision-maker within the internationalization process of SMEs has extensively been acknowledged in the International Entrepreneurship field. Yet, despite this, the current discourse is mainly limited to socio-demographics, and social and human capital, and does not seem to advance towards the influence and role of, e.g., deeper-level personality aspects on the SME’s internationalization process. Findings are scattered across different fields of research and disciplines, making it difficult to build upon existing knowledge. To address this, we execute a Systematic Literature Review focusing on internationalization, SMEs, and personality, with specific attention for deeper-level personality aspects. Our findings reveal a rather young body of literature which uses a behavioral perspective, and can be subdivided into three overarching research themes: Internationalization Behaviors, Internationalization Initiation, and Internationalization Performance. Our thematic analysis and cross-thematic discussion provide a fertile ground for further studies on the entrepreneur’s deeper-level personality aspects in relation to SME internationalization. In the future research section, we recommend the exploration of alternative behavioral theories, and multi-level and holistic approaches to further explore this promising sub-domain.

Beyond English: Considering Language and Culture in Psychological Text Analysis

The paper discusses the role of language and culture in the context of quantitative text analysis in psychological research. It reviews current automatic text analysis methods and approaches from the perspective of the unique challenges that can arise when going beyond the default English language. Special attention is paid to closed-vocabulary approaches and related methods (and Linguistic Inquiry and Word Count in particular), both from the perspective of cross-cultural research where the analytic process inherently consists of comparing phenomena across cultures and languages and the perspective of generalizability beyond the language and the cultural focus of the original investigation. We highlight the need for a more universal and flexible theoretical and methodological grounding of current research, which includes the linguistic, cultural, and situational specifics of communication, and we provide suggestions for procedures that can be implemented in future studies and facilitate psychological text analysis across languages and cultures.

The Language of Creativity: Validating Linguistic Analysis to Assess Creative Scientists and Artists

The purpose of this study was twofold: first, to be among the first attempts to validate linguistic analysis as a method of creativity assessment and second, to differentiate between individuals in varying scientific and artistic creativity levels using personality language patterns. Creativity is most commonly assessed through methods such as questionnaires and specific tasks, the validity of which can be weakened by scorer or experimenter error, subjective and response biases, and self-knowledge constraints. Linguistic analysis may provide researchers with an automatic, objective method of assessing creativity, and free from human error and bias. The current study used 419 creativity text samples from a wide range of creative individuals mostly in science (and some in the arts and humanities) to investigate whether linguistic analysis can, in fact, distinguish between creativity levels and creativity domains using creativity dictionaries and personality dimension language patterns, from the linguistic inquiry and word count (LIWC) text analysis program. Creative individuals tended to use more words on the creativity keyword dictionaries as well as more introversion and openness to experience language pattern words than less creative individuals. Regarding creativity domains, eminent scientists used fewer introversion, and openness to experience language pattern words than eminent artists. Text analysis through LIWC was able to partially distinguish between the three creativity levels, in some cases, and the two creativity domains (science and art). These findings lend support to the use of linguistic analysis as a partially valid assessment of scientific and artistic creative achievement.

Do You Get What I Mean?!? The Undesirable Outcomes of (Ab)Using Paralinguistic Cues in Computer-Mediated Communication

The shift to working from home, which has intensified due to Covid-19, increased our reliance on communication technology and the need to communicate effectively via computer-mediated communication and especially via text. Paralinguistic cues, such as repeated punctuation, are used to compensate for the lack of non-verbal cues in text-based formats. However, it is unclear whether these cues indeed bridge the potential gap between the writer's intentions and the reader's interpretations. A pilot study and two experiments investigated the effect of using repeated punctuation on behavioral intention to assist an email writer in a work-related situation. Findings demonstrate that while the intentions behind using repeated punctuation relate to signaling situational importance or affective state, behavioral intentions are driven by dispositional rather than situational attributions. Specifically, the use of repeated punctuation reduces perceived competence of the message writer and consequently decreases positive behavioral intentions. Overall, the study challenges the simplified view of paralinguistic cues as communication facilitators, highlighting their potential harmful effects on impression formation and behavioral intentions in the digital age.

Multilingual Transformer-Based Personality Traits Estimation

Intelligent agents have the potential to understand personality traits of human beings because of their every day interaction with us. The assessment of our psychological traits is a useful tool when we require them to simulate empathy. Since the creation of social media platforms, numerous studies dealt with measuring personality traits by gathering users’ information from their social media profiles. Real world applications showed how natural language processing combined with supervised machine learning algorithms are effective in this field. These applications have some limitations such as focusing on English text only and not considering polysemy in text. In this paper, we propose a multilingual model that handles polysemy by analyzing sentences as a semantic ensemble of interconnected words. The proposed approach processes Facebook posts from the myPersonality dataset and it turns them into a high-dimensional array of features, which are then exploited by a deep neural network architecture based on transformer to perform regression. We prove the effectiveness of our work by comparing the mean squared error of our model with existing baselines and the Kullback–Leibler divergence between the relative data distributions. We obtained state-of-the-art results in personality traits estimation from social media posts for all five personality traits.

Friends with text as data benefits: Assessing and extending the use of automated text analysis in political science and political psychology

Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre-processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of sentiment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics.

A Semantic Corpus Comparison Analysis of Couple-Focused Interventions for Problematic Alcohol Use

Incorporating spouses into interventions for problematic alcohol use is associated with increased efficacy; yet, little is known about the therapeutic processes that may explain these effects. In a study of partner language use during couple-focused alcohol interventions, we utilized a linguistic corpus comparison tool, Wmatrix, to identify semantic themes that differentiated couples with successful and unsuccessful treatment outcomes and may therefore also reflect potential change processes. Thirty-three couples participated in a randomized control trial of Family Systems Therapy (FST) or Cognitive Behavioural Therapy (CBT). Linguistic comparisons of partners' speech during the therapy sessions suggested that drinks and alcohol was a significant differentiating semantic theme. Specifically, patients and spouses in FST with successful outcomes used more language related to drinks and alcohol than patients and spouses in FST with unsuccessful outcomes. Post-hoc analyses of context suggested that, in FST, successful spouses spoke less about the patient's drinking and more about alcohol in general (without reference to an individual) than unsuccessful spouses. Conversely, spouses in CBT with successful outcomes used less language related to drinks and alcohol than spouses in CBT with unsuccessful outcomes. In CBT, successful spouses spoke more about the patient's and couple's drinking and less about the spouse's and other people's drinking than unsuccessful spouses. Results emphasize the role of spouse behaviour-in this case indexed via language use-in alcohol treatment outcomes. Findings also suggest potentially distinct therapeutic processes in FST and CBT and highlight the utility of linguistic corpus comparison methods in couple-focused intervention research. Copyright © 2016 John Wiley & Sons, Ltd.

KEY PRACTITIONER MESSAGE

Incorporating spouses into interventions for problematic alcohol use is associated with increased efficacy; yet, little is known about the specific therapeutic processes that may explain these effects. Findings from this study suggest that semantic themes such as drinks and alcohol in partner speech during therapy sessions differentiate successful and unsuccessful treatment outcomes among couples participating in two couple-focused interventions for problematic alcohol use. In addition, the context in which partners used alcohol-related language differed by intervention type and treatment outcome, which suggests potential therapeutic processes that are unique to the two interventions (Family Systems versus Cognitive Behavioural Therapy).

Personality expression in Chinese language use

To date, little research has investigated personality expressions in languages other than English. Given that the Chinese language has the largest number of native speakers in the world, it is vitally important to examine the associations between personality and Chinese language use. In this research, we analysed Chinese microblogs and identified word categories and factorial structures associated with personality traits. We also compared our results with previous findings in English and showed that linguistic expression of personality has both universal- and language-specific aspects. Expression of personality via content words is more likely to be consistent across languages than expression via function words. This makes an important step towards uncovering universal patterns of personality expression in language.

Social Media Analyses for Social Measurement

Demonstrations that analyses of social media content can align with measurement from sample surveys have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or "found" social media content. But just how trustworthy such measurement can be-say, to replace official statistics-is unknown. Survey researchers and data scientists approach key questions from starting assumptions and analytic traditions that differ on, for example, the need for representative samples drawn from frames that fully cover the population. New conversations between these scholarly communities are needed to understand the potential points of alignment and non-alignment. Across these approaches, there are major differences in (a) how participants (survey respondents and social media posters) understand the activity they are engaged in; (b) the nature of the data produced by survey responses and social media posts, and the inferences that are legitimate given the data; and (c) practical and ethical considerations surrounding the use of the data. Estimates are likely to align to differing degrees depending on the research topic and the populations under consideration, the particular features of the surveys and social media sites involved, and the analytic techniques for extracting opinions and experiences from social media. Traditional population coverage may not be required for social media content to effectively predict social phenomena to the extent that social media content distills or summarizes broader conversations that are also measured by surveys.

How do personality traits affect communication among users in online social networks?

Purpose

– The purpose of this work is to analyse the relationships between the personality traits of linked users in online social networks. First the authors tried to discover relation patterns between personality dimensions in conversations. They also wanted to verify some hypotheses: whether users' personality is stable throughout different conversation threads and whether the similarity-attraction paradigm can be verified in this context. They used the five factor model of personality or Big Five, which has been widely studied in psychology.

Design/methodology/approach

– One of the approaches to detect users' personalities is by analysing the language they use when they talk to others. Based on this assumption the authors computed users' personality from the conversations extracted from the MySpace social network. Then the authors analysed the relationships among personality traits of users to discover patterns.

Findings

– The authors found that there are patterns between some personality dimensions in conversation threads, for example, agreeable people tend to communicate with extroverted people. They confirmed that the personality stability theory can be verified in social networks. Finally the authors could verify the similarity-attraction paradigm for some values of personality traits, such as extroversion, agreeableness, and openness to experience.

Originality/value

– The results the authors found provide some clues about how people communicate within online social networks, particularly who they tend to communicate with depending on their personality. The discovered patterns can be used in a wide range of applications, such as suggesting contacts in online social networks. Although some studies have been made regarding the role of personality in social media, no similar analysis has been done to evaluate how users communicate in social media considering their personality.

Depression and Self-Focused Language in Structured Interviews with Older Men

The association between depression and self-focused language has been found to varying extents across studies. The presence or absence of the association may depend on the communicative context. Based on Beck's depression model, a broad, evaluative self-focused question was predicted more likely to elicit a stronger association than a full interview containing a more heterogeneous question set of items. The spontaneous speech obtained during structured interviews of 26 depressed and nondepressed older men, an as-yet little studied population, was analyzed. Results were consistent with the hypothesis that association between self-focused language and depression was demonstrated in the target question but not across the entire interview. The results may explain some of the aforementioned discrepancies in prior studies.

A Positivity Bias in Written and Spoken English and Its Moderation by Personality and Gender

The human tendency to use positive words ("adorable") more often than negative words ("dreadful") is called the linguistic positivity bias. We find evidence for this bias in two studies of word use, one based on written corpora and another based on naturalistic speech samples. In addition, we demonstrate that the positivity bias applies to nouns and verbs as well as adjectives. We also show that it is found to the same degree in written as well as spoken English. Moreover, personality traits and gender moderate the effect, such that persons high on extraversion and agreeableness and women display a larger positivity bias in naturalistic speech. Results are discussed in terms of how the linguistic positivity bias may serve as a mechanism for social facilitation. People, in general, and some people more than others, tend to talk about the brighter side of life.

Electronic Person Perception

Previous studies of blogging and e-mail correspondence have focused on how writers express personality traits and emotion in their writing. This study complements these earlier studies by focusing on how these messages are perceived by others. A total of 166 undergraduate students made judgments about the senders of e-mails in which the person (first vs. third) that the message was written in was manipulated along with the presence or absence of expressive punctuation and typographical errors. Messages written in the third person were perceived as angrier and more likely to be written by someone in a supervisory relationship with the recipient of the e-mail, and the presence or absence of question marks and/or exclamation points was a strong determinant of the judgments that were made about the sender’s emotional state and relationship with the recipient. Messages with a high frequency of expressive punctuation were also more likely to be perceived as having been written by a female. The results suggest that stylistic features of e-mail messages may be an overlooked but influential component of people’s reactions to the electronic discourse that they have with others.

Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers

Previous studies have found systematic associations between personality and individual differences in word use. Such studies have typically focused on broad associations between major personality domains and aggregate word categories, potentially masking more specific associations. Here I report the results of a large-scale analysis of personality and word use in a large sample of blogs (N=694). The size of the dataset enabled pervasive correlations with personality to be identified for a broad range of lexical variables, including both aggregate word categories and individual English words. The results replicated category-level findings from previous offline studies, identified numerous novel associations at both a categorical and single-word level, and underscored the value of complementary approaches to the study of personality and word use.

Revealing Dimensions of Thinking in Open-Ended Self-Descriptions: An Automated Meaning Extraction Method for Natural Language

A new method for extracting common themes from written text is introduced and applied to 1,165 open-ended self-descriptive narratives. Drawing on a lexical approach to personality, the most commonly-used adjectives within narratives written by college students were identified using computerized text analytic tools. A factor analysis on the use of these adjectives in the self-descriptions produced a 7-factor solution consisting of psychologically meaningful dimensions. Some dimensions were unipolar (e.g., Negativity factor, wherein most loaded items were negatively valenced adjectives); others were dimensional in that semantically opposite words clustered together (e.g., Sociability factor, wherein terms such as shy, outgoing, reserved, and loud all loaded in the same direction). The factors exhibited modest reliability across different types of writ writing samples and were correlated with self-reports and behaviors consistent with the dimensions. Similar analyses with additional content words (adjectives, adverbs, nouns, and verbs) yielded additional psychological dimensions associated with physical appearance, school, relationships, etc. in which people contextualize their self-concepts. The results suggest that the meaning extraction method is a promising strategy that determines the dimensions along which people think about themselves.