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Most Central (Degree) Words in Individuals' Networks

Most Central (Degree) Words in Individuals' Networks

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People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the...

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... strongly overlapped in content with each other and with existing SWOW data sets. Table 2 ...

Citations

... For instance, there are citizen science projects that collect free associations (i.e., what are the first three words that come to mind for the concept "dog"?) through an online word association game-these free associations are commonly analyzed as semantic networks Dubossarsky et al., 2017). Others have adopted a snowballing approach to collect free associations to estimate the semantic network structure of individuals (Morais et al., 2013;Wulff et al., 2021). Others have used the verbal fluency or semantic fluency task (i.e., name as many members of the "animal" category) to estimate semantic network structures (Borodkin et al., 2016;Kenett et al., 2013). ...
Article
Cognitive scientists have a long-standing interest in quantifying the structure of semantic memory. Here, we investigate whether a commonly used paradigm to study the structure of semantic memory, the semantic fluency task, as well as computational methods from network science could be leveraged to explore the underlying knowledge structures of academic disciplines such as psychology or biology. To compare the knowledge representations of individuals with relatively different levels of expertise in academic subjects, undergraduate students (i.e., experts) and preuniversity high school students (i.e., novices) completed a semantic fluency task with cue words corresponding to general semantic categories (i.e., animals, fruits) and specific academic domains (e.g., psychology, biology). Network analyses of their fluency networks found that both domain-general and domain-specific semantic networks of undergraduates were more efficiently connected and less modular than the semantic networks of high school students. Our results provide an initial proof-of-concept that the semantic fluency task could be used by educators and cognitive scientists to study the representation of more specific domains of knowledge, potentially providing new ways of quantifying the nature of expert cognitive representations.
... Similarly, Wulff, Hills, and Mata, (2018) examined the semantic networks of younger and older adults and found that the networks of older adults showed smaller average degree and longer path lengths than younger adults. Researchers suggest that the age-related differences in semantic network structure are a consequence of having more lived experiences (Siew et al., 2019;Wulff, Hills, & Mata, 2018;Wulff, De Deyne, Aeschbach, & Mata, 2021). ...
... Considerable research has demonstrated that environmental factors, including cumulative environmental exposure and different environments, contribute to age differences in human cognition (Siew et al., 2019;Wulff, De Deyne, Aeschbach, & Mata, 2021;Wulff, De Deyne, Jones, & Mata, 2019). Individuals continue to learn as they get older. ...
... Individuals continue to learn as they get older. Older people are assumed to have acquired more knowledge (e.g., broader vocabulary) than younger people, and subsequently leads to the concepts become more distant and further apart from each other in their mental representation (Cosgrove et al., 2021;Wulff, De Deyne, Aeschbach, & Mata, 2021). This may account for the pattern observed in older adults' semantic network and the similar segregated effect in face Fig. 3. 2D visualization of the age generation-based face preference networks. ...
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How does aging affect facial attractiveness? We tested the hypothesis that people find older faces less attractive than younger faces, and furthermore, that these aging effects are modulated by the age and sex of the perceiver and by the specific kind of attractiveness judgment being made. Using empirical and computational network science methods, we confirmed that with increasing age, faces are perceived as less attractive. This effect was less pronounced in judgments made by older than younger and middle-aged perceivers, and more pronounced by men (especially for female faces) than women. Attractive older faces were perceived as elegant more than beautiful or gorgeous. Furthermore, network analyses revealed that older faces were more similar in attractiveness and were segregated from younger faces. These results indicate that perceivers tend to process older faces categorically when making attractiveness judgments. Attractiveness is not a monolithic construct. It varies by age, sex, and the dimensions of attractiveness being judged.
... Similarly, Wulff, Hills, and Mata, (2018) examined the semantic networks of younger and older adults and found that the networks of older adults showed smaller average degree and longer path lengths than younger adults. Researchers suggest that the age-related differences in semantic network structure are a consequence of having more lived experiences (Siew et al., 2019;Wulff, Hills, & Mata, 2018;Wulff, De Deyne, Aeschbach, & Mata, 2021). ...
... Considerable research has demonstrated that environmental factors, including cumulative environmental exposure and different environments, contribute to age differences in human cognition (Siew et al., 2019;Wulff, De Deyne, Aeschbach, & Mata, 2021;Wulff, De Deyne, Jones, & Mata, 2019). Individuals continue to learn as they get older. ...
... Individuals continue to learn as they get older. Older people are assumed to have acquired more knowledge (e.g., broader vocabulary) than younger people, and subsequently leads to the concepts become more distant and further apart from each other in their mental representation (Cosgrove et al., 2021;Wulff, De Deyne, Aeschbach, & Mata, 2021). This may account for the pattern observed in older adults' semantic network and the similar segregated effect in face Fig. 3. 2D visualization of the age generation-based face preference networks. ...
Article
Full-text available
How does aging affect facial attractiveness? We tested the hypothesis that people find older faces less attractive than younger faces, and furthermore, that these aging effects are modulated by the age and sex of the perceiver and by the specific kind of attractiveness judgment being made. Using empirical and computational network science methods, we confirmed that with increasing age, faces are perceived as less attractive. This effect was less pronounced in judgments made by older than younger and middle-aged perceivers, and more pronounced by men (especially for female faces) than women. Attractive older faces were perceived as elegant more than beautiful or gorgeous. Furthermore, network analyses revealed that older faces were more similar in attractiveness and were segregated from younger faces. These results indicate that perceivers tend to process older faces categorically when making attractiveness judgments. Attractiveness is not a monolithic construct. It varies by age, sex, and the dimensions of attractiveness being judged.
... Thus, a similar analysis as conducted in our study at the individual level would be helpful. While currently still a challenge, a few methods have been proposed to estimate individual-based semantic networks (Morais et al., 2013;Zemla et al., 2016;Benedek et al., 2017;He et al., 2020;Wulff et al., 2021). Thus, follow up research is needed to estimate individual-based semantic networks related to the concepts of beauty and wellness, to replicate and extend our current findings. ...
Article
Full-text available
Beauty and wellness are terms used often in common parlance, however their meaning and relation to each other is unclear. To probe their meaning, we applied network science methods to estimate and compare the semantic networks associated with beauty and wellness in different age generation cohorts (Generation Z, Millennials, Generation X, and Baby Boomers) and in women and men. These mappings were achieved by estimating group-based semantic networks from free association responses to a list of 47 words, either related to Beauty, Wellness, or Beauty + Wellness. Beauty was consistently related to Elegance, Feminine, Gorgeous, Lovely, Sexy, and Stylish. Wellness was consistently related Aerobics, Fitness, Health, Holistic, Lifestyle, Medical, Nutrition, and Thrive. In addition, older cohorts had semantic networks that were less connected and more segregated from each other. Finally, we found that women compared to men had more segregated and organized concepts of Beauty and Wellness. In contemporary societies that are preoccupied by the pursuit of beauty and a healthy lifestyle, our findings shed novel light on how people think about beauty and wellness and how they are related across different age generations and by sex.
... We present data of a proof-of-concept study of MySWOW involving four younger and four older individuals. For additional details of the study rationale, see Wulff et al. (2021, February 15). ...
Preprint
Full-text available
We report data from a proof-of-concept study involving the concurrent assessment of large-scale individual semantic networks and cognitive performance. The data include 10,800 free associations-collected using a dedicated web-based platform over the course of 2-4 weeks-and responses to several cognitive tasks, including verbal fluency, episodic memory, associative recall tasks, from four younger and four older native German speakers. The data are unique in scope and composition and shed light on individual and age-related differences in mental representations and their role in cognitive performance across the lifespan.