Which of the “big five” personality dimensions refers to being talkative and energetic?

Big Five Personality Traits

As stated earlier, MBTI has attracted criticism in recent years. The proposed alternative by most critics is the big five personality traits. The five-factor model [FFM], which the big five personality traits is based on, was developed by several researchers throughout the past decades, including Norman [1967], Smith [1967], Goldberg [1981], and McCrae and Costa [1987].11 The key strength claimed by the FFM model is that it is based on empirical research that shows consistency across time, culture, and age groups. It is also considered more structured because the five traits do not overlap. At a high level, the traits are [Figure 8.2]:

Openness to experience: People with a strong tendency in this trait are considered to be imaginative and creative. They are willing to try new things and are open to ideas.

Conscientiousness: People with a strong tendency in this trait are considered to be goal focused and organized and have self-discipline. They follow rules and plan their actions.

Extraversion: People with a strong tendency in this trait are considered to be outgoing and energetic. They obtain their energy from the company of other people and are defined as being assertive and enthusiastic.

Agreeableness: People with a strong tendency in this trait are considered to be compassionate, kind, and trustworthy. They value getting along with other people and are tolerant.

Neuroticism: People with a strong tendency in this trait are considered to be anxious, self-conscious, impulsive, and pessimistic. They experience negative emotions relatively easily.

There also have been studies that investigate applying the FFM to software engineering teams.12,13 These studies focus on multiple roles within a software team and not particularly on software architects. However, they do look at key traits for software designers. Based on their analysis, the key trait that has to be strong for software architects is agreeableness. This result supports the Continuous Architecture view that at least 50% of the role of an architect is to focus on communication. [We discuss this in detail in Chapter 9.] The other traits that we think are important for architects are openness to experience and conscientiousness.

It is interesting to note that most of these studies do not explicitly define the role of an architect but refer to the role of a software designer. We are not particularly concerned about the difference between what we would call a solution architect and a software designer. The main differences are in the scale they are operating in. The role of a software designer can be said to happen at a lower level of granularity than a solution architect. Regardless, both are involved in making architecture or design decisions related to a software product. Because we have already stated that Continuous Architecture also applies to the dimension of scale, then both roles should reflect similar capabilities and responsibilities.

Narcissism and Twitter

While narcissism is associated with social media usage in various genres as noted above, it is especially associated with Twitter usage. This section will review various findings. It is too bad that we cannot tweet these results as we are writing this for more narcissistic coverage. McKinney, Kelley, and Duran [2012] argue that Twitter is a good venue for narcissists because it allows them to answer the question, “What are you doing?” in terms of 140 characters or less. Followers are supposedly interested in one’s moment-to-moment postings, which suggests egocentrism, self-aggrandizement, and self-importance—the very characteristics of narcissistic individuals. Their study revealed that being open about sharing information about oneself was significantly related to the frequency of using Facebook and Twitter to provide self-focused updates, while high scores on narcissism were associated with a larger number of Facebook friends and with the number of self-focused “tweets” that people send. In addition, posting selfies on social media is another reflection of narcissism [Murray, 2015].

The Big Five personality traits are stable, primordial personality traits that consist of neuroticism, openness, conscientiousness, extraversion, and agreeableness [Cobb-Clark & Schurer, 2012; Honeycutt et al., 2013; McCrae & Terracciano, 2005]. Openness reflects the degree of intellectual curiosity, creativity, and preference for novelty and variety. Conscientiousness is the predisposition to show self-discipline and refers to planning, organization, and dependability. Extraversion reflects the need to seek stimulation in the company of others, sociability, and talkativeness. Agreeableness is the tendency to be compassionate and cooperative towards others. Finally, neuroticism reveals the tendency to experience negative emotions such as anger, anxiety, depression, or vulnerability. Neuroticism reflects emotional stability and control of impulses.

McCain and Campbell [2016] summarize a few findings on the Big Five traits and social media usage. They indicate how the traits associated with narcissism reflect a trait model of narcissism as opposed to a state or situational model in which people are narcissistic in some platforms and less narcissistic in others. In Big Five terms, grandiose narcissism is associated with high levels of extraversion and openness and low levels of agreeableness [Miller et al., 2011]. Extraverts have larger social networks in general [Pollet, Roberts, & Dunbar, 2011; Roberts, Wilson, Fedurek, & Dunbar, 2008] and spend more time and generate more content on social media sites [Gosling, Augustine, Vazire, Holtzman, & Gaddis, 2011]. Thus narcissists’ tendency to have more friends and generate more content on social media may be associated with their extraversion. Conversely, vulnerable narcissism is associated with low agreeableness and neuroticism. These findings suggest that anxiety is associated with increased social media usage.

Qiu, Lin, Ramsay, and Yang [2012] measured the “Big Five” personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism among 142 Twitter users. They analyzed their participants’ tweets over a month-long period and used a software program called Linguistic Inquiry and Word Count to look for patterns in the language they used. They found that extraverts used more assent words, fewer functional words, and fewer impersonal pronouns. Openness was negatively related to the use of adverbs, swear words, affect words, and nonfluent words, but positively related to prepositions. When Qiu and his colleagues asked those who had never met the Twitter users to judge their personalities based only on their Twitter feeds, they found that people could accurately judge two of the Big Five dimensions—neuroticism and agreeableness.

Path Analysis for Twin Research

Behavior genetics uses quantitative genetic analysis as a tool. Quantitative genetic analysis is the theoretical basis for the statistical analysis of variation in populations. The statistical tool is more commonly known under the names “structural equation modeling” or “path analysis.” Model estimation has many advantages over the classic approach. The graphical reproduction of structural models is very helpful for making the assumptions of the twin design more explicit [see Fig. 1]. Using path models makes it possible to test different models against each other and to opt for the model that best fits the data. The fit of the model can be expressed in goodness-of-fit statistics and the estimates for genetic and environmental effects are given together with their standard errors.

Many different complex and multivariate models are already commonly used, but here quantitative genetic analysis using the most basic univariate model for genetic analysis is illustrated. This model can easily be extended to multivariate and longitudinal designs as well as designs that go beyond the twin design and investigate the more complex genetic and environmental relationships between different relatives.

Figure 1 represents the simplest path model for MZ and DZ twins reared together. The genetic theory as outlined above is reflected in the model. By convention, the observed or dependent variables are drawn as rectangles and the latent, independent variables are shown as circles. Single-headed arrows are used to define causal relations or paths and double-headed arrows are used to define covariances. Also by convention, uppercase letters are used to define the latent variables and lowercase letters are used to represent the paths and double-headed arrows. An example from research on extraversion is used to illustrate the model. Extraversion is one of the Big Five personality traits. It is associated with active, impulsive, and social behavior, where people who exhibit high levels of these behaviors are called extraverts and people who exhibit low levels of these behaviors are called introverts. The variables in the squares are the observed levels of extraversion for twin 1 and co-twin 2. The latent variables [circles] come from behavior genetic theory. E stands for the unique environment and by definition random error is incorporated in E; A stands for the additive genetic effects, D stands for the effects of dominant genes and epistasis, and C stands for the effects of the common environment. The covariation between both genetic effects is defined for MZ as well as for DZ twins; where MZ twins show a correlation of 1, they are of the same genotype and DZ twins show a correlation of 0.5 for additive genetic effects and 0.25 for dominance effects.

Since quantitative genetic analysis has a strong regression component, the model can be also defined from its underlying regression structures

P1=eE1+aA1+dD1+cC1,

and

P2=eE2+a A2+dD2+cC2,

where P1 and P2 are the phenotypes of two co-twins. As can be derived from the regression equation, the phenotype is assumed to be a linear function of the underlying genetic and environmental effects. The total variance of the observed measure is composed from the factor loadings as:

Vp=a2+d2+c2+e2.

In the classical twin study that uses twins that are reared together, C and D cannot be modeled in one analysis, because then they become confounded and the model cannot be identified. Using this path diagram, different models can be tested. First, the simplest model that takes only the unique environmental and additive genetic effects into account is examined. In the second step, this model can be extended with common environmental or dominance effects, depending on the difference between the intraclass correlations of the MZ and DZ twins in the sample. When the intraclass correlation of the MZ twins is less than twice the intraclass correlation of the DZ twins, a model that allows for common environmental effects is chosen, because the DZ twins resemble each other more than could be expected on the basis of their genotype alone. When the intraclass correlation of the MZ twins is larger than twice the intraclass correlation of the DZ twins, a model that allows for dominance effects is chosen, because the DZ twins differ more than could be expected from theory. Finally, a model that excludes every genetic effect, the CE model that states that all individual differences are attributable to environmental effects, can be chosen.

Using these three models, the way that models are compared and tested is discussed here. In Table I, the path estimates, as well as the goodness-of-fit measure [here, the normed fit index], are given. In the study here examined, the intraclass correlation for MZ twin pairs was 0.5 and for DZ twin pairs it was 0.39, which could be an indication of common environmental effects.

Table I. Results of a Univariate Quantitative Genetic Analysis on Extraversion

Note: AE, model includes additive genetic and unique environmental effects. ACE, model includes additive genetic and unique and common environmental effects. CE, model includes only environmental effects. VA, phenotypic variance explained by genetic effects. VE, phenotypic variance explained by unique environmental effects. VC, phenotypic variance explained by common environmental effects. NFI, normed fit index for large samples. AIC, Akiaki's information criterion.

These results show that a model that incorporates only additive genetic and unique environmental effects has a nice fit [χ2/df