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The Personality Profile of LinkedIn Users
Abstracts
with Cattell’s Culture Fair Test. A RT factor and a P3 factor were extracted by employing a PCA across complexity levels. There was no significant correlation between the factors. Commonality analysis was used to determine the proportions of unique and shared variance in intelligence explained by the RT and P3 latency factors. RT and P3 latency explained 5.5% and 5% of unique variance in intelligence. However, the two speed factors did not explain a significant portion of shared variance. This result suggests that RT and P3 latency in the Hick paradigm are measuring different aspects of information processing that explain different parts of variance in intelligence.
479
different samples. The aim of the present study was to investigate the factor structure of the Dark Triad Dirty Dozen in a large sample of residents of the United States. Participants (N = 3500) were recruited through Amazon’s Mechanical Turk. Besides the Dark Triad Dirty Dozen (Jonason & Webster, 2010), participants answered demographical questions pertaining age, gender, religion, education, and salary and the Short Dark Triad (Jones & Paulhus, 2014). Moreover, a subsample of 500 participants have also answered the following measures: Eysenck Personality Questionnaire Revised (Eysenck, Eysenck & Barret, 1985), the Mach-IV (Christie & Geis, 1970), and the Narcissistic Personality Inventory - short version (NPI- 16).
doi:10.1016/j.paid.2016.05.139 doi:10.1016/j.paid.2016.05.141
Self-Esteem and Appearance Related Comparisons: Assimilation and Contrast Effects in Post-Secondary Students E. Galati The current study investigated two moderators that may account for assimilation and contrast effects in response to appearance comparisons: self-esteem and appearance relevance. A sample of 92 post-secondary female students completed measures of selfesteem, appearance relevance, appearance satisfaction, and state affect. Participants were then exposed to one of three images: highly attractive women (upward comparisons), highly unattractive women (downward comparisons), or neutral images (no comparisons). Participants were then instructed to complete two post-test measures: appearance satisfaction and state affect. Results found a significant interaction between self-esteem and comparison conditions. Women with low self-esteem (LSE) showed reduced appearance satisfaction after exposure to upward comparisons and increased appearance satisfaction after viewing downward comparisons; however, no significant effects were found for women with high selfesteem (HSE). No significant interactions were found for appearance relevance. However, a main effect was found between appearance relevance and appearance satisfaction, in which women with high appearance relevance had lower scores of appearance satisfaction. Thus, results seem to suggest that appearance related comparisons have a stronger effect on females with LSE while those with HSE seemed to be relatively unaffected.
The Personality Profile of LinkedIn Users D. Garcia, A. Al nima The Big-Five model of personality is one of the most accepted personality models and comprises five dimensions with underlying facets: Openness (Facets: fantasy, aesthetics, feelings, actions, ideas, and values), Conscientiousness (Facets: competence, order, dutifulness, achievement striving, self- discipline, and deliberation), Extraversion (Facets: warmth, gregariousness, Assertiveness, activity, excitement-seeking, and positive emotions), Agreeableness (Facets: trust, straightforwardness, altruism, compliance, modesty, and tender-mindedness), and Neuroticism (Facets: anxiety, angry and hostility, depression, self-consciousness, impulsiveness, and vulnerability). Nevertheless, although the Big-Five has been regarded as a good basis for the design of tests for use in recruitment situations, factor analysis suggest that it has its limitations when screening personnel—a sixth factor related to individual’s prior knowledge about the job has been found to appear. In recent years, social networks have gained importance in recruitment situations. The present study investigated the factor structure and personality profiles of Swedish users of LinkedIn (http://www. linkedin.com), which is a website mainly used for professional networking. A total of 566 participants answered to demographic questions and the NEO Personality Inventory-Revised. We conducted a factor analysis using structural equation modeling to estimate the dimensions of the Big Five. In addition, the scores in the dimensions and facets of LinkedIn users were compared to that of the normal population.
doi:10.1016/j.paid.2016.05.140 doi:10.1016/j.paid.2016.05.142 Factor Structure of a Short Measure of the Dark Triad Traits D. Garcia Studies using behavior genetic approaches show that the Dark Triad traits (i.e., Machiavellianism, Narcissism, and Psychopathy) expand some of the current personality models (Veselka, Schermer, & Vernon, 2012). This triad “share a tendency to be callous, selfish, and malevolent in their interpersonal dealings” (Paulhus & Williams, 2002, p. 100). In personality research, brief scales are used to avoid response fatigue among participants. One such scale is the Dark Triad Dirty Dozen (Jonason & Webster, 2010), which is composed of 12 items (Likert scale: 1 = not at all; 7 = very much); 4 for each Dark Triad trait: psychopathy (e.g., “I tend to lack remorse”), narcissism (e.g., “I tend to want others to admire me”), and Machiavellianism (e.g., “I have used deceit or lied to get my way”). Nevertheless, brief scales risk sacrifice precision and need to be validated across
Personality Descriptions and Personality Measures D. Garcia, P. Rosenberg, S. Sikström Research on individual differences in personality assumes that person characteristics are reflected in language. Nevertheless, previous research has used personality-descriptive words clustered by small number of experts and idiosyncratic criteria and methods (Leising et al., 2014). In this study, laypeople were asked to freely generate words that describe their own personality. The aim was to provide a larger set of words people actually use to describe themselves and to investigate the relationship between these personality-descriptive words and psychometric measures of personality. A total of six samples, with a total of 3000 participants, were collected through Amazon’s Mechanical Turk. Besides
with Cattell’s Culture Fair Test. A RT factor and a P3 factor were extracted by employing a PCA across complexity levels. There was no significant correlation between the factors. Commonality analysis was used to determine the proportions of unique and shared variance in intelligence explained by the RT and P3 latency factors. RT and P3 latency explained 5.5% and 5% of unique variance in intelligence. However, the two speed factors did not explain a significant portion of shared variance. This result suggests that RT and P3 latency in the Hick paradigm are measuring different aspects of information processing that explain different parts of variance in intelligence.
479
different samples. The aim of the present study was to investigate the factor structure of the Dark Triad Dirty Dozen in a large sample of residents of the United States. Participants (N = 3500) were recruited through Amazon’s Mechanical Turk. Besides the Dark Triad Dirty Dozen (Jonason & Webster, 2010), participants answered demographical questions pertaining age, gender, religion, education, and salary and the Short Dark Triad (Jones & Paulhus, 2014). Moreover, a subsample of 500 participants have also answered the following measures: Eysenck Personality Questionnaire Revised (Eysenck, Eysenck & Barret, 1985), the Mach-IV (Christie & Geis, 1970), and the Narcissistic Personality Inventory - short version (NPI- 16).
doi:10.1016/j.paid.2016.05.139 doi:10.1016/j.paid.2016.05.141
Self-Esteem and Appearance Related Comparisons: Assimilation and Contrast Effects in Post-Secondary Students E. Galati The current study investigated two moderators that may account for assimilation and contrast effects in response to appearance comparisons: self-esteem and appearance relevance. A sample of 92 post-secondary female students completed measures of selfesteem, appearance relevance, appearance satisfaction, and state affect. Participants were then exposed to one of three images: highly attractive women (upward comparisons), highly unattractive women (downward comparisons), or neutral images (no comparisons). Participants were then instructed to complete two post-test measures: appearance satisfaction and state affect. Results found a significant interaction between self-esteem and comparison conditions. Women with low self-esteem (LSE) showed reduced appearance satisfaction after exposure to upward comparisons and increased appearance satisfaction after viewing downward comparisons; however, no significant effects were found for women with high selfesteem (HSE). No significant interactions were found for appearance relevance. However, a main effect was found between appearance relevance and appearance satisfaction, in which women with high appearance relevance had lower scores of appearance satisfaction. Thus, results seem to suggest that appearance related comparisons have a stronger effect on females with LSE while those with HSE seemed to be relatively unaffected.
The Personality Profile of LinkedIn Users D. Garcia, A. Al nima The Big-Five model of personality is one of the most accepted personality models and comprises five dimensions with underlying facets: Openness (Facets: fantasy, aesthetics, feelings, actions, ideas, and values), Conscientiousness (Facets: competence, order, dutifulness, achievement striving, self- discipline, and deliberation), Extraversion (Facets: warmth, gregariousness, Assertiveness, activity, excitement-seeking, and positive emotions), Agreeableness (Facets: trust, straightforwardness, altruism, compliance, modesty, and tender-mindedness), and Neuroticism (Facets: anxiety, angry and hostility, depression, self-consciousness, impulsiveness, and vulnerability). Nevertheless, although the Big-Five has been regarded as a good basis for the design of tests for use in recruitment situations, factor analysis suggest that it has its limitations when screening personnel—a sixth factor related to individual’s prior knowledge about the job has been found to appear. In recent years, social networks have gained importance in recruitment situations. The present study investigated the factor structure and personality profiles of Swedish users of LinkedIn (http://www. linkedin.com), which is a website mainly used for professional networking. A total of 566 participants answered to demographic questions and the NEO Personality Inventory-Revised. We conducted a factor analysis using structural equation modeling to estimate the dimensions of the Big Five. In addition, the scores in the dimensions and facets of LinkedIn users were compared to that of the normal population.
doi:10.1016/j.paid.2016.05.140 doi:10.1016/j.paid.2016.05.142 Factor Structure of a Short Measure of the Dark Triad Traits D. Garcia Studies using behavior genetic approaches show that the Dark Triad traits (i.e., Machiavellianism, Narcissism, and Psychopathy) expand some of the current personality models (Veselka, Schermer, & Vernon, 2012). This triad “share a tendency to be callous, selfish, and malevolent in their interpersonal dealings” (Paulhus & Williams, 2002, p. 100). In personality research, brief scales are used to avoid response fatigue among participants. One such scale is the Dark Triad Dirty Dozen (Jonason & Webster, 2010), which is composed of 12 items (Likert scale: 1 = not at all; 7 = very much); 4 for each Dark Triad trait: psychopathy (e.g., “I tend to lack remorse”), narcissism (e.g., “I tend to want others to admire me”), and Machiavellianism (e.g., “I have used deceit or lied to get my way”). Nevertheless, brief scales risk sacrifice precision and need to be validated across
Personality Descriptions and Personality Measures D. Garcia, P. Rosenberg, S. Sikström Research on individual differences in personality assumes that person characteristics are reflected in language. Nevertheless, previous research has used personality-descriptive words clustered by small number of experts and idiosyncratic criteria and methods (Leising et al., 2014). In this study, laypeople were asked to freely generate words that describe their own personality. The aim was to provide a larger set of words people actually use to describe themselves and to investigate the relationship between these personality-descriptive words and psychometric measures of personality. A total of six samples, with a total of 3000 participants, were collected through Amazon’s Mechanical Turk. Besides