scholarly journals When Figurative Language Goes off the Rails and under the Bus: Fluid Intelligence, Openness to Experience, and the Production of Poor Metaphors

2021 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Paul J. Silvia ◽  
Roger E. Beaty

The present research examined the varieties of poor metaphors to gain insight into the cognitive processes involved in generating creative ones. Drawing upon data from two published studies as well as a new sample, adults’ open-ended responses to different metaphor prompts were categorized. Poor metaphors fell into two broad clusters. Non-metaphors—responses that failed to meet the basic task requirements—consisted of “adjective slips” (describing the topic adjectivally instead of figuratively), “wayward attributes” (attributing the wrong property to the topic), and “off-topic idioms” (describing the wrong topic). Bad metaphors—real metaphors that were unanimously judged as uncreative—consisted of “exemplary exemplars” (vehicles that lacked semantic distance and thus seemed trite) and “retrieved clichés” (pulling a dead metaphor from memory). Overall, people higher in fluid intelligence (Gf) were more likely to generate a real metaphor, and their metaphor was less likely to be a bad one. People higher in Openness to Experience, in contrast, were more likely to generate real metaphors but not more or less likely to generate bad ones. Scraping the bottom of the response barrel suggests that creative metaphor production is a particularly complex form of creative thought.

2013 ◽  
Vol 34 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Sophie von Stumm

Intelligence-as-knowledge in adulthood is influenced by individual differences in intelligence-as-process (i.e., fluid intelligence) and in personality traits that determine when, where, and how people invest their intelligence over time. Here, the relationship between two investment traits (i.e., Openness to Experience and Need for Cognition), intelligence-as-process and intelligence-as-knowledge, as assessed by a battery of crystallized intelligence tests and a new knowledge measure, was examined. The results showed that (1) both investment traits were positively associated with intelligence-as-knowledge; (2) this effect was stronger for Openness to Experience than for Need for Cognition; and (3) associations between investment and intelligence-as-knowledge reduced when adjusting for intelligence-as-process but remained mostly significant.


2016 ◽  
Vol 32 (3) ◽  
pp. 628 ◽  
Author(s):  
Tatiana De Cassia Nakano ◽  
Ricardo Primi ◽  
Walquiria De Jesus Ribeiro ◽  
Leandro S. Almeida

<p class="Abstract">We test the utility of the Battery for Giftedness Assessment (BaAH/S) in identifying differences in two groups of already known gifted students in the areas of academic and artistic talents. Four latent factors were assessed (a) fluid intelligence, (b) metaphor production (verbal creativity), (c) figural fluency (figural creativity), and (d) divergent thinking figural task quality (figural creativity). A sample of 987 children and adolescents, 464 boys and 523 girls, of ages ranging from 8 to 17 of two groups: regular students (N=866) and gifted students (N= 67 academic abilities, N=34 artistic abilities and N=20 no domain identified). Academic giftedness group of have higher reasoning, can produce more remote/original metaphors, high figural fluency and drawings rated as more original. Children in the group of artistic giftedness have higher reasoning, high figural fluency and drawings rated as more original. Reasoning abilities are relatively higher in academic giftedness group than artistic (<em>r </em>= .39 vs <em>r </em>=.14). Within artistic group figural fluency and ratings of originality are relatively more important than reasoning (<em>r </em>= .25 and <em>r</em> = .21 vs .14). We emphasizes the importance of assessing creativity in different domains in addition to intelligence to improve the understanding of giftedness and talent.</p>


HUMANIS ◽  
2018 ◽  
pp. 125
Author(s):  
I Gede Agus Krisna Permana ◽  
I Ketut Wandia ◽  
I Made Rajeg

Figurative language can appear in various types and the meaning may not be determined by its components. This study aims to identify and analyze the meaning of figurative language found in the song lyrics “Passenger's album all the little lights”. There are two theories used in this study. The first is the theory of figurative language proposed by Knickerbocker and Reninger, and the second is the theory of meaning by Leech as the supporting theory. The data in this study were directly taken from Passenger’s fourth album. The album consists of twelve songs. They were collected by documentation method and note taking technique. The collected data were analyzed  using qualitative and descriptive method. This study applied informal method to present the analysis. The result of this study shows that there are nine types of figurative language found in song lyrics. They were allusion, simile, metaphor, irony, personification, hyperbole, dead metaphor, metonymy, and paradox. Most of the figurative expressions found in those songs were similes. Four out of seven types of meaning used in those lyrics in order to understand the figurative meaning in the song lyrics; they were connotative meaning, conceptual meaning, affective meaning, and collocative meaning. All the songs which are analyzed have the main theme about life and love.


JURNAL ELINK ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 40
Author(s):  
Moh. Nurman ◽  
Lidia Dindiana

The aims of this research is to know the types of metaphors found in Bring Me The Horizon’s “Amo” album selected song’s lyrics and what is the intended meaning of the song’s lyrics. There are two research questions. They are: 1) what types of metaphors are found in Bring Me the Horizon’s selected song lyrics? 2) What is the intended meaning of the song’s lyrics? The reason behind this research was conduct is to get more knowledge about figurative language especially metaphor and how it works in the literary world. This research uses descriptive qualitative method in analyzing the lyrics. The result of this research shows six types of metaphors by Newmark. Those are dead, cliché, stock, recent, original metaphor and simile. Two out of their three songs of Bring Me the Horizon, that is Medicine and In the Dark use dead metaphor and simile the most. It is then concluded that the intended meanings of their three songs is to tell other people who ever felt belittled, have social issues or being looked down to keep going and not affected by those hurtful words. In other words, Bring Me the Horizon uses the function of figurative language especially metaphor to express their message and applied them into their works.  Keywords: Metaphor, meaning


Author(s):  
Kadek Ayu Ekasani

This writing is entitled “The Use of Figurative Expression in Novel ‘The Doomsday Conspiracy’ by Sidney Sheldon”. The discussion is focussed on the analysis of figurative expression in the novel. This study is aimed to identify the types of figurative expression found in the novel and to determine the meaning represented by the use of figurative expression in the novel. The novel entitled “The Doomsday Conspiracy” by Sidney Sheldon is chosen as the data source for this writing. The main theory is adopted from the book “Interpreting Literature” by Knickerbocker and Reninger (1963) about the theory of figurative language, namely about simile, metaphor, personification, synecdoche, hyperbole, metonymy, paradox, irony, dead metaphor, and allusion as a frame or reference. There are also some supporting theories, such as Halliday’s theory (1985) about the metaphorical modes of expressions and Leech’s theory (1974) about seven types of meanings. The finding of the analysis shows that the figurative expression used in the novel can be divided into three groups: (a) comparison included simile, metaphor and personification; (b) contradiction included hyperbole; and (c) connection included metonymy and allusion. But among these types of figurative expression, the groups of comparison, simile, metaphor and personification are those commonly applied in the novel, because they are used to describe the persona’s having a deep feeling which is brought by the main character in the novel.


2017 ◽  
Vol 38 (2) ◽  
pp. 563-571
Author(s):  
Xiqin Liu ◽  
Ling Liu ◽  
Zhencai Chen ◽  
Yiying Song ◽  
Jia Liu

2017 ◽  
Author(s):  
Julien Dubois ◽  
Paola Galdi ◽  
Yanting Han ◽  
Lynn K. Paul ◽  
Ralph Adolphs

AbstractPersonality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging data from 884 young healthy adults in the Human Connectome Project (HCP) database. We attempted to predict personality traits from the “Big Five”, as assessed with the NEO-FFI test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two inter-subject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; 3 denoising strategies; 2 alignment schemes; 3 models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=0.24, R2=0.024) almost as well as we could predict the score on a 24-item intelligence test (PMAT24_A_CR: r=0.26, R2=0.044). Other factors (Extraversion, Neuroticism, Agreeableness and Conscientiousness) yielded weaker predictions across results that were not statistically significant under permutation testing. We also derived two superordinate personality factors (“α” and “β”) from a principal components analysis of the NEO-FFI factor scores, thereby reducing noise and enhancing the precision of these measures of personality. We could account for 5% of the variance in the β superordinate factor (r=0.27, R2=0.050), which loads highly on Openness to experience. We conclude with a discussion of the potential for predicting personality from neuroimaging data and make specific recommendations for the field.


2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S75-S75
Author(s):  
Zarina Bilgrami ◽  
Elkin Gutierrez ◽  
Cansu Sarac ◽  
Cheryl Corcoran ◽  
Guillermo Cecchi

Abstract Background Clinicians have long observed peculiarities in the use of figurative language by individuals with schizophrenia, as part of larger expressive deficits. Natural language processing has been used to predict psychosis onset (Bedi et al., 2015; Corcoran et al., 2018), identifying classifiers such as semantic coherence. Here we examine use of metaphor across the psychosis spectrum. Methods Participant groups across the psychosis spectrum (healthy controls, clinical high risk for psychosis and individuals with schizophrenia) participated in open-ended interviews lasting approximately one hour and encouraged to express themselves narratively. Each interview was transcribed, then deidentified and run through the metaphor analysis algorithm. The results were then used to determine an overall metaphor frequency rate for each participant/transcript. Results The algorithm detected a significantly higher proportion of the words in transcripts of patients with schizophrenia as metaphorical (6.5%) than in healthy controls’ transcripts (5.7%) (p &lt; 0.01, t57 = 2.68). Patients in the CHR group also produced more metaphorical words tagged by the algorithm (6.6%; p &lt; 0.01, t95 = 3.69). Discussion These results demonstrate that metaphor usage, as measured using automated algorithms, is a robust and powerful indicator of symptoms, whether defined via current schizophrenia diagnosis or by clinical high-risk status. The ability to estimate metaphoric content in speech and written samples can be a significant contribution to the systemization of psychosis symptoms and and may be useful as a screen for the general population to identify individuals who may be at risk for psychosis.


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