scholarly journals EXPRESS: People With Larger Social Networks Show Poorer Voice Recognition

2021 ◽  
pp. 174702182110307
Author(s):  
Shiri Lev-Ari

The way we process language is influenced by our experience. We are more likely to attend to features that proved to be useful in the past. Importantly, the size of individuals’ social network can influence their experience, and consequently, how they process language. In the case of voice recognition, having a larger social network might provide more variable input and thus enhance the ability to recognize new voices. On the other hand, learning to recognize voices is more demanding and less beneficial for people with a larger social network as they have more speakers to learn yet spend less time with each. This paper tests whether social network size influences voice recognition, and if so, in which direction. Native Dutch speakers listed their social network and performed a voice recognition task. Results showed that people with larger social networks were poorer at learning to recognize voices. Experiment 2 replicated the results with a British sample and English stimuli. Experiment 3 showed that the effect does not generalize to voice recognition in an unfamiliar language suggesting that social network size influences attention to the linguistic rather than non-linguistic markers that differentiate speakers. The studies thus show that our social network size influences our inclination to learn speaker-specific patterns in our environment, and consequently the development of skills that rely on such learned patterns, such as voice recognition.

2020 ◽  
Author(s):  
Jiyin Cao ◽  
Edward Bishop Smith

Previous research has demonstrated that the size and reach of people’s social networks tend to be positively related to their social status. Although several explanations help to account for this relationship—for example, higher-status people may be part of multiple social circles and therefore have more social contacts with whom to affiliate—we present a novel argument involving people’s beliefs about the relationship between status and quality, what we call status-quality coupling. Across seven separate studies, we demonstrate that the positive association between social status and network-broadening behavior (as well as social network size) is contingent on the extent to which people believe that status is a reliable indicator of quality. Across each of our studies, high- and low-status people who viewed status and quality as tightly coupled differed in their network-broadening behaviors, as well as in the size of their reported social networks. The effect was largely driven by the perceived self-value and perceived receptivity of the networking target. Such differences were significantly weaker or nonexistent among equivalently high- and low-status people who viewed status as an unreliable indicator of quality. Because the majority of participants—both high- and low-status—exhibited beliefs in status-quality coupling, we conclude that such a belief marks an important and previously unaccounted-for driver of the relationship between status, network-broadening behaviors, and social networks. Implications for research on social capital, advice seeking, and inequality are highlighted in the discussion section.


Autism ◽  
2019 ◽  
Vol 24 (5) ◽  
pp. 1138-1151
Author(s):  
Jiedi Lei ◽  
Chris Ashwin ◽  
Mark Brosnan ◽  
Ailsa Russell

Transitioning to university can be anxiety-provoking for all students. The relationship between social anxiety, autistic traits and students’ social network structure, and perceived support is poorly understood. This study used a group-matched design where autistic students ( n = 28) and typically developing students ( n = 28) were matched on sex, age (17–19 years), ethnicity, pre-university academic performance and degree subject at university. Autistic students reported greater transition to university worries, and a smaller social network size compared to typically developing students, though perceived similar levels of support from their social networks. Autistic and typically developing students showed differential patterns of association with both autistic traits and social anxiety. Broader clinical and practical implications of findings are discussed.


2016 ◽  
Vol 37 (8) ◽  
pp. 990-1011 ◽  
Author(s):  
Scott R. Beach ◽  
Richard Schulz ◽  
Rodlescia Sneed

Social support and social networks are important correlates of elder mistreatment. This study tests hypothesized associations between perceived social support, social network size, and financial exploitation (FE). A population-based survey of 903 older adults (60+) in Allegheny County (Pittsburgh, Pennsylvania) found that lower perceived social support and larger social networks were simultaneously associated with higher risk for FE since age 60, controlling for known risk factors. The same associations were found for FE in the last 6 months. Older adults with larger social networks combined with lower perceived social support were most likely to report FE. When it comes to the role of social relationships and risk for FE, “more may not always be better.” Encouragement to widen the social network by “making new friends” should be stressed less than making sure these new network members will truly be supportive of the older adult.


2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 115-115
Author(s):  
Candyce H. Kroenke ◽  
Yvonne Michael ◽  
Xiao-Ou Shu ◽  
Elizabeth Poole ◽  
Marilyn L. Kwan ◽  
...  

115 Background: Larger social networks have been associated with better breast cancer survival. To investigate potential mediators, we evaluated associations of social network size and diversity with lifestyle and treatment factors associated with prognosis. Methods: We included 9,331 women from the After Breast Cancer Pooling Project who provided data on social networks within two years following diagnosis. A social network index was derived from information about the presence of a spouse or intimate partner, religious ties, community participation, friendship ties, and numbers of relatives. Diversity was assessed as variety of ties, independent of size. We used logistic regression to evaluate associations with outcomes and evaluated whether effect estimates differed using meta-analytic techniques. Results: Associations of social networks and outcomes generally did not differ by cohort. Because of the low prevalence of smoking and alcohol consumption in the Shanghai cohort, however, analyses of smoking and alcohol included US cohorts only. Women who were socially isolated (small networks) were more likely to be obese (body mass index>30 kg/m2, OR=1.21, 95% CI:1.03-1.42) and have low physical activity (<10 MET-h/wk, OR=1.53, 95% CI:1.34-1.75) compared to socially integrated women. Women with low network diversity were more likely to be current smokers (OR=3.68, 95% CI:2.19-6.19) and have high alcohol consumption (>15 g/d alcohol, OR=2.43, 95% CI:1.60-3.69). Among node positive cases, socially isolated women were more likely not to receive chemotherapy (OR=1.52, 95% CI:1.03-2.25). By contrast, low network diversity, but not social network size, was associated with greater odds of not receiving adjuvant hormonal therapy (OR=1.52, 95% CI:1.03-2.23). Associations with surgery were nonsignificant. Conclusions: In a large pooled cohort, small, less diverse social networks measured post-diagnosis were associated with more adverse lifestyle factors and less intensive cancer treatment, which may help to explain poorer breast cancer prognosis in socially isolated women.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S929-S930
Author(s):  
Ethan Siu Leung Cheung ◽  
Kedong Ding

Abstract Background: Previous studies have found older adults’ cognitive functions are strongly associated with their social networks, including memory. Yet, few studies have explored the influences of specific social network members, such as siblings and children. Further, little studies examined the impact of the size of older adults’ social networks. Hence, this study aimed to investigate how older adults’ relationships with their spouses, siblings, and children, as well as the size of their social networks, affect American older adults’ memory functions. Methods: Using the 2018 data from NHATS, 5547 samples were included. We adopted a multiple logistic regression model to test the impact of social support network sizes, and how associations of social support networks varied between spouses, siblings, and children. All models were calibrated for age, gender, education, income, and race/ethnicity. Results: Analysis showed that higher socioeconomic status (more education and without Medicaid), being female, and younger age were associated with increased odds of having good self-rated memory functions. Older adults with larger social support networks (&gt;=3 individuals) were more likely to have better self-rated memory function (adjusted odds ratio, 1.182, p&lt;0.05), while holding other variables. Having a spouse also increased odds of higher self-rating memory function, in contrast to having children. Conclusion: This study highlighted the importance of having a larger social network size for older adult’s memory function and indicated the necessity of developing intervention programs to expand older adults' social network size, especially for those with lower socioeconomic status.


2018 ◽  
Vol 10 (10) ◽  
pp. 3380 ◽  
Author(s):  
Miaomiao Yin ◽  
Asghar Jahanshahi

Entrepreneurs’ social networks play a crucial role in developing knowledge-based resources for their new ventures. Although most studies in an entrepreneurship context find that trust is very important when entrepreneurs develop social networks, limited research examines how trust can explain the variation in the relationship between an entrepreneur’s social networks and a firm’s knowledge-based resources. Therefore, the major objective of the paper is to understand the effects of the size of an entrepreneur’s social network on his or her firm’s knowledge-based resources with high and low levels of trust. Our data were collected from surveys administered to 476 entrepreneurs in China in 2018. Our multiple regression analysis indicates that social networks reinforce knowledge-based resources in a situation where entrepreneurs highly trust their major networks partners in their business environment (e.g., family, close friends, consultants, suppliers, peers, etc.). However, with a low level of trust, the relationship between social network and knowledge-based resources is curvilinear (inverse U-shaped). Our empirical validations showed that the relationship between social network and a firm’s knowledge-based resources is highly contingent to the level of trust among network members.


2017 ◽  
Vol 45 (4) ◽  
pp. 551-562 ◽  
Author(s):  
Ying Chen ◽  
Xiaohu Zhou ◽  
Guojun Yang ◽  
Jiani Bao ◽  
Guan Wang

Although findings reported in an increasing number of studies shed light on the relationship between optimism and entrepreneurial outcomes, little is known of the mechanisms by which entrepreneurial optimism influences new venture performance. Researchers have found that people who are highly optimistic build more extensive social networks than others do, which can influence the outcome of their efforts. In order to explore the relationships among entrepreneurial optimism, social networks, and new venture performance, we analyzed data obtained from 142 Chinese entrepreneurs. Results indicated that entrepreneurial optimism had a significant impact on social network size, social network heterogeneity, and new venture performance. Social network size fully mediated the relationship between entrepreneurial optimism and new venture performance, but social network heterogeneity did not have a mediating role. These findings support the application of a social network perspective to gain a better understanding of the mechanism by which entrepreneurial optimism influences new venture performance.


2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S162-S162
Author(s):  
Kali Defever ◽  
Sarah L Patrick ◽  
Jennifer E Layden ◽  
Scott Fletcher ◽  
Brent Van Ham ◽  
...  

Abstract Background Hepatitis C virus (HCV) infection rates have increased among younger, rural persons nationally. We report on a preliminary sample of a study examining HCV acquisition risk factors among rural persons who inject drugs (PWID) or person who use opioids (PWUO) non-medically. Methods We used respondent-driven sampling (RDS) to recruit PWID/PWUO in southern, rural Illinois as part of a larger study on infectious disease rates among social networks of PWID and illicit opioid users. Participants were surveyed regarding drug and sexual risk behavior, healthcare access, stigma, and social networks, and underwent rapid screening for HCV (OraQuickÒ HCV Rapid Antibody Test) and other infections. Using R software, we generated descriptive statistics to characterize HCV prevalence. Results Between July 2018 and April 2019,135 current PWID/PWUO were recruited, screened, and surveyed (58.5% male; 82.2% white; mean age 40.1 years). HCV rapid tests detected antibodies (HCV+) among 53 of 112 screened (47.3%). HCV+ participants were more likely to be white (96.2% vs. 83.1%, P = 0.006) than HCV antibody negative (HCV-) participants and showed a bimodal age distribution with peaks in the 25–30 and 45–50 age ranges. Reported injection drug use and heroin use in the past 30 days was significantly more common among HCV+ participants (96.2% vs. 72.9%, P = 0.001, and 12.9 vs. 7.9 days, P = 0.024) While HCV+ participants less frequently used methamphetamine compared with HCV -participants, the use of that drug was still high in both groups (11.9 vs. 18.4 days of use in the past 30 days, P = 0.01). HCV+ participants reported fewer social network members than HCV- participants (2.2 vs. 3.0, P = 0.048). Conclusion In this analysis of a preliminary sample, HCV exposure was high; with those positive for HCV antibody showing a bimodal age distribution, high frequency of multiple drug use, and smaller social network size compared with HCV negative counterparts. Upon RDS-based enrollment completion and pending analysis we will further examine HIV RNA status as well as the specific associations between network size and other risk factors that may inform disease screening and treatment interventions. Disclosures All authors: No reported disclosures.


2018 ◽  
Vol 71 (10) ◽  
pp. 2249-2260 ◽  
Author(s):  
Shiri Lev-Ari

Infants and adults learn new phonological varieties better when exposed to multiple rather than a single speaker. This article tests whether having a larger social network similarly facilitates phonological performance. Experiment 1 shows that people with larger social networks are better at vowel perception in noise, indicating that the benefit of laboratory exposure to multiple speakers extends to real life experience and to adults tested in their native language. Furthermore, the experiment shows that this association is not due to differences in amount of input or to cognitive differences between people with different social network sizes. Follow-up computational simulations reveal that the benefit of larger social networks is mostly due to increased input variability. Additionally, the simulations show that the boost that larger social networks provide is independent of the amount of input received but is larger if the population is more heterogeneous. Finally, a comparison of “adult” and “child” simulations reconciles previous conflicting findings by suggesting that input variability along the relevant dimension might be less useful at the earliest stages of learning. Together, this article shows when and how the size of our social network influences our speech perception. It thus shows how aspects of our lifestyle can influence our linguistic performance.


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