Covid-19 medförde storskalig övergång till studier och arbete på distans. Fysiska möten ersattes av digitala möten. Syftet var att undersöka inverkan av personlighet och situationsuppfattning på nivån av engagemang under digitala möten. Totalt 149 studenter och förvärvsarbetande, varav 98 kvinnor och 51 män, besvarade en enkät som mätte självskattad nivå av engagemang i relation till situationsperception (RSQ-8*) och personlighetsdrag (Big Five). Den genomsnittliga engagemangsnivån under digitala möten motsvarade cirka 71%. Äldre deltagare skattade engagemanget högre än yngre och förvärvsarbetande högre än studenter. Uppfattningen om digitala möten som en positiv situation var en genomgående signifikant prediktor för högre nivåer av engagemang. Regressionsanalyser visade att av totalt 38% förklarad variation i engagemang under digitala möten, svarade personlighet för 8% och situationsperception för 21%. Bakgrundsvariablerna kön, ålder och sysselsättning svarade för resterande 9%. Framtida studier uppmanas undersöka interaktionseffekten mellan personlighet och situationsperception på engagemang, samt beteendeutfall när fysiska situationer ersätts av digitala alternativ.

Yes / Trait inferences occur routinely and rapidly during social interaction, sometimes based on scant or fleeting information. In this research, participants (perceivers) made inferences of targets' big‐five traits after briefly watching or listening to an unfamiliar target (a third party) performing various mundane activities (telling a scripted joke or answering questions about him/herself or reading aloud a paragraph of promotional material). Across three studies, when perceivers judged targets to be either low or high in one or more dimensions of the big‐five traits, they tended to be correct, but they did not tend to be correct when they judged targets as average. Such inferences seemed to vary in effectiveness across different trait dimensions and depending on whether the target's behaviour was presented either in a video with audio, a silent video, or just in an audio track—perceivers generally were less often correct when they judged targets as average in each of the big‐five traits across various information channels (videos with audio, silent videos, and audios). Study 3 replicated these findings in a different culture. We conclude with discussion of the scope and the adaptive value of this trait inferential ability.

This study explores the relevance of the Big Five personality traits ;openness, conscientiousness, extraversion, agreeableness, and neuroticism; for project managers in their professional roles. By conducting a systematic review of existing literature, the research aims to understand how these traits potentially contribute to various aspects of project leadership. Findings indicate that while each trait offers specific advantages for managing projects, no single trait encompasses all necessary managerial skills. The study suggests that combinations of these traits can influence leadership capabilities, reflecting the complexity of personality's role in effective project management. For example, traits such as extraversion and agreeableness may enhance communication and team dynamics, whereas conscientiousness may correlate with planning and risk management efficiencies. However, further research is needed to draw definitive conclusions about the specific impacts of each trait. The study highlights the importance of viewing personality traits from a broader perspective, where they interact to contribute to the diverse competencies required for successful project management.

LinkedIn profiles are increasingly serving as supplements to or substitutes for traditional resumes. Beyond the explicit information in LinkedIn profiles, research indicates that recruiters and hiring managers can infer additional applicant characteristics. The Big Five personality dimensions are particularly valuable for organizations to glean from these profiles due to their relationship with job performance. Although previous research has attempted to predict personality from LinkedIn, it has severe limitations, including limited practical utility due to relying on manual coding of profiles, inconsistent and largely non-significant findings, and a tendency to overlook the text data within profiles. This study addresses the first issue by developing an automated computer coding process, which significantly reduces profile coding time. The other limitations are tackled by drawing on the Realistic Accuracy Model and literature suggesting natural language contains personality cues to create a more comprehensive prediction model by incorporating the text data of LinkedIn profiles. Machine learning was used to analyze the profiles of 960 employees recruited through CloudResearch Connect and MTurk. Cross-validated and tested on out-of-sample data, the results indicate that all the Big Five personality dimensions can be validly and reliably predicted from LinkedIn profiles when text data is incorporated and analyzed through open-vocabulary approaches, but generally not when text is not included. Additionally, the built models result in fewer subgroup differences than a traditional self-report personality assessment. This research provides a more efficient and accurate approach to predicting personality from LinkedIn profiles. The implications and limitations of the developed approach are discussed.

Syftet med denna studie var att undersöka om det fanns ett samband mellan alkoholkonsumtion och personlighetsdimensionerna som beskrivits utifrån Femfaktorteorin samt mellan variablerna kön, ålder, civilstatus och antal barn. Vidare var studiens syfte att undersöka om dessa variabler kan predicera alkoholkonsumtion. Deltagarna (N=140) studerade vid ett medelstort universitet i södra Sverige.  Korrelationsanalysen          påvisade samband mellan alkoholkonsumtion, extraversion, agreeableness, kön, civilstatus och antal barn deltagarna hade. I en multipel regressionsanalys försvann sambandet med agreeableness och civilstatus. / The purpose of this study was to examine associations between alcohol consumption and the personality dimensions specified in the Five factor theory as well as between the variables sex, age, civil status and number of children. Furthermore was an aim to examine if these variables could predict alcohol consumption. The participants (N=140) were students from a midsized university in southern Sweden. Correlation analysis demonstrated a connection between alcohol consumption, extraversion, agreeableness, sex, civil status, and the number of children the participants had. The connection between agreeableness and alcohol consumption as well as between alcohol consumption and civil status disappeared in the follow up multiple regression analysis.

Previous studies have shown that the FFM factor neuroticism was negatively correlated with Need for Cognition. Anxiety has been shown to be highly correlated with neuroticism. It has also been shown that women tend to score higher on both neuroticism and anxiety. Need for Cognition has been shown to predict long term academic success. This study aims to contribute to the current understanding of anxiety, neuroticism and Need for Cognition by examining these three constructs together. The study will also analyzes how gender can affect the relationships between the constructs. 272 participants responded to three questionnaires measuring the constructs. 86 were men, 183 were women and 3 defined themselves as "other". 246 of the respondents were university students and 26 responded did not currently study at university. Results indicate that anxiety is a negative predictor for Need for Cognition. This is speculated to be because anxiety has an effect on working memory which in turn is associated with Need for Cognition. Gender differences are significant regarding all three constructs. Findings are complicated by a negative suppressor effect. Results, limitations, and future research are discussed. / Tidigare studier har visat att FFM faktorn neuroticism var negativt korrelerad med Need for Cognition. Ångest har visat sig vara starkt korrelerat med neuroticism. Det har också visat sig att kvinnor tenderar att skatta högre på både neuroticism och ångest. Need for Cognition har visat sig förutsäga långsiktig akademisk framgång. Denna studie syftar till att bidra till aktuell kunskap om ångest, neuroticism och Need for Cognition genom att undersöka dessa tre konstrukt tillsammans. Studien analyserar också hur kön påverkar relationerna mellan konstruktionerna. 272 deltagare svarade på tre enkäter som mäter dessa konstrukt. 86 var män, 183 kvinnor och 3 definierade sig som "övrigt". 246 av de svarande var universitetsstuderande och 26 svarande studerade inte för närvarande på universitet. Resultaten tyder på att ångest kan vara en negativ prediktor för Need for Cognition. Detta spekuleras kunna bero på att ångest har en effekt på arbetsminnet, som i sin tur kan påverka Need for Cognition. Det fanns signifikanta könsskillnader gällande alla tre konstrukt. Resultaten kompliceras av en negativ suppressor effekt. Resultat, begränsningar och framtida forskning diskuteras.

This study investigates if different personality types are connected to different motives for Instagram use. 187 participants with 150 females and 44 men were part of this study and they were recruited through a Facebook group. The findings were that there was no gender differences in the use of Instagram and that the most frequent motive for Instagram use was “Surveillance/knowledge about others”. People who scored high on the neurotic personality trait tended to use Instagram with “surveillance” as their motive, while extraverted people tend to use Instagram with “documentation” as their motive. People who score high on  openness mostly used Instagram with “creativity” as their motive, and people spend mostly 5 to 1 hour a day on the application. The conclusion is that different personality traits are connected to different motives for Instagram use but not all of the five in the Big Five. The ones that were connected to different motives were extraversion, openness and neuroticism. Conscientiousness and agreeableness had no connection to any of the motives. / Denna studie undersöker skillnader i personlighetstyper kopplat till olika motiv för Instagram-användning. 194 personer har deltagit i studien varav 150 stycken kvinnor och 44 män och de blev rekryterade via en Facebook-grupp. Inga könsskillnader i användandet av Instagram hittades och det främsta motivet för användning var "övervakning/kunskap om andra". Personer som har mycket av personlighetsdraget neuroticism tenderar att använda Instagram med "dokumentation" som deras motiv, och personer som har mycket av openness tenderar att ha "kreativitet" som deras motiv för Instagram-användning. Personer spenderar generellt 5 minuter till en timme om dagen i appen. Slutsatser som dras är att personer med olika personlighetstyper har olika motiv för användandet av Instagram men inte alla personlighetstyper i Femfaktorteorin. Personer som hade mycket av personlighetsdraget conscientiousness eller agreeableness hade ingen koppling till något av motiven.

Made available in DSpace on 2016-03-22T17:26:59Z (GMT). No. of bitstreams: 1 jaciana.pdf: 667514 bytes, checksum: 543d150a01c06b10933602382c393667 (MD5) Previous issue date: 2012-01-12 / The Big Five theory has been the basis for much of the personality assessment work conducted recently. Currently this is the theory that provides a better understanding of personality. The Big Five inventory- 10 (BFI-10) is a scale composed of 10 items that assesses five dimensions of personality, with two items for each factor: Extroversion, Agreeableness, Conscientiousness, Neuroticism and Openness. The purpose of this study due to the need for a brief instrument based on Big Five Theory for use in research in Brazil. Were interviewed 1158 people, being the majority female (58%) aged between 14 and 35 years. In the original form of the instrument was added one item in each factor to select later the 10 items with better psychometric qualities. There was evidence of construct validity and the rates of internal consistence were acceptable. At the end of the analysis it was identified that Neuroticism was the factor that demonstrated greater legitimacy, whereas Agreeableness was the less representative. Associations were observed among factors and the sociodemographic variables: gender, age and scholarity. It has been concluded that the adapted BFI-10 can be used when the time available is very limited. Considering the limitations of a so brief scale, the results should be interpreted cautiously. Further studies should be made to complement the psychometric characteristics of the scale / Recentemente a teoria Big Five tem servido de base para grande parte do trabalho de avaliação da personalidade. O Big Five Inventory 10 (BFI-10) é uma escala de 10 itens (dois a cada fator), que avalia cinco dimensões da personalidade: Extroversão; Amabilidade; Conscienciosidade; Neuroticismo e Abertura a experiências. A adaptação de um instrumento baseado no BFI-10 foi o propósito do presente estudo, em função da necessidade de um instrumento breve baseado na teoria Big Five para uso em pesquisas no Brasil. Foram entrevistadas 1158 pessoas, 58% do sexo feminino, com idades entre 14 e 35 anos. À forma original do instrumento foi acrescentado um item em cada fator para selecionar posteriormente os 10 com melhores resultados. As evidências de validade de construto e os índices de fidedignidade foram aceitáveis. O fator Neuroticismo teve os melhores resultados, enquanto Amabilidade foi o menos representativo. Foram observadas associações entre os fatores e as variáveis sóciodemográficas: gênero, idade e escolaridade. Concluiu-se que a escala baseada no BFI-10 poderá ser utilizada quando o tempo disponível for muito limitado. Considerando as limitações de uma escala breve, os resultados devem ser interpretados com precaução. Novos estudos devem ser feitos para complementar as características psicométricas da escala

Sistemas de Geração de Língua Natural tentam produzir textos de maneira automatizada. Em sistemas desse tipo, é desejável produzir textos de forma realista - ou psicologicamente plausível - como forma de aumentar o engajamento do leitor. Uma das formas de alcançar esse objetivo é gerando textos de modo a refletir uma personalidade-alvo de interesse. Por exemplo, uma pessoa extrovertida usaria palavras mais simples e seus textos teriam mais interjeições e traços de oralidade. Esse trabalho tem o objetivo de desenvolver um modelo de reescrita sentencial para o português brasileiro com base em traços de personalidade de um locutor-alvo. Para isso, foi coletado um córpus de textos e inventários de personalidade e, com base em uma análise preliminar desses dados, foram encontrados fortes indícios de correlação entre os fatores de personalidade e as características observadas dos textos em português brasileiro. Foram gerados três modelos de lexicalização, referentes à adjetivos, substantivos e verbos. Esses modelos de lexicalização, então, foram utilizados na proposta de um modelo de reescrita sentencial para selecionar as palavras mais adequadas à personalidade-alvo. Os resultados demonstram que o uso de personalidade permite que o texto gerado seja mais próximo do desempenho humano se comparado a um sistema de baseline que faz escolhas lexicais mais frequentes / Natural Language Generation Systems attempt to produce texts in an automated fashion. In systems of this kind, it is desired to produce texts realisticaly - or at least psychologically plausible - as a way to increase reader\'s engagement. One way to achieve this goal is generating texts in such a way to reflect a target personality profile. For example, an extroverted individual would use simpler words and its texts would have more interjections and orality traces. This work proposes the development of a Brazilian Portuguese personality-based sentence rewrite model. To this end, a corpus with text samples and personality inventories has been collected, and, based on a preliminary analysis, strong correlations between personality and text features have been found. Three lexicalization models were generated, related to adjectives, nouns and verbs. These models were then used by the sentence rewrite model to select the most appropriate word for the target personality. Results show that the usage of personality allows the generated text to be closer to human performance when compared to a baseline system that makes lexical choices based on frequency

Sistemas de Geração de Língua Natural tentam produzir textos de maneira automatizada. Em sistemas desse tipo, é desejável produzir textos de forma realista - ou psicologicamente plausível - como forma de aumentar o engajamento do leitor. Uma das formas de alcançar esse objetivo é gerando textos de modo a refletir uma personalidade-alvo de interesse. Por exemplo, uma pessoa extrovertida usaria palavras mais simples e seus textos teriam mais interjeições e traços de oralidade. Esse trabalho tem o objetivo de desenvolver um modelo de reescrita sentencial para o português brasileiro com base em traços de personalidade de um locutor-alvo. Para isso, foi coletado um córpus de textos e inventários de personalidade e, com base em uma análise preliminar desses dados, foram encontrados fortes indícios de correlação entre os fatores de personalidade e as características observadas dos textos em português brasileiro. Foram gerados três modelos de lexicalização, referentes à adjetivos, substantivos e verbos. Esses modelos de lexicalização, então, foram utilizados na proposta de um modelo de reescrita sentencial para selecionar as palavras mais adequadas à personalidade-alvo. Os resultados demonstram que o uso de personalidade permite que o texto gerado seja mais próximo do desempenho humano se comparado a um sistema de baseline que faz escolhas lexicais mais frequentes / Natural Language Generation Systems attempt to produce texts in an automated fashion. In systems of this kind, it is desired to produce texts realisticaly - or at least psychologically plausible - as a way to increase reader\'s engagement. One way to achieve this goal is generating texts in such a way to reflect a target personality profile. For example, an extroverted individual would use simpler words and its texts would have more interjections and orality traces. This work proposes the development of a Brazilian Portuguese personality-based sentence rewrite model. To this end, a corpus with text samples and personality inventories has been collected, and, based on a preliminary analysis, strong correlations between personality and text features have been found. Three lexicalization models were generated, related to adjectives, nouns and verbs. These models were then used by the sentence rewrite model to select the most appropriate word for the target personality. Results show that the usage of personality allows the generated text to be closer to human performance when compared to a baseline system that makes lexical choices based on frequency