Dynamics of social network emergence explain network evolution

Pomeroy, C. D.; Bond, Robert M.; Mucha, Peter J.; Cranmer, Skyler J.

doi:10.1038/s41598-020-78224-2

Cited by 5 publications

(2 citation statements)

References 48 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Just as frequent contact fosters research collaborations among established researchers 13 , adviceseeking behavior among medical students may be an early indicator of research literacy and future collaboration. However, quantifying and analyzing these dynamic interactions presents a challenge.…”

Section: Discussionmentioning

confidence: 99%

Exploring Advice-Seeking Dynamics in Undergraduate Medical Research: A Social Network Analysis

Jarukasemkit,

Yoadsanit,

Teansue

et al. 2024

Preprint

View full text Add to dashboard Cite

Purpose Research achievement thrives on collaboration, often facilitated by mentorship. To understand how these meaningful interactions promote research productivity, this study investigates the dynamics of undergraduate peer-to-peer and student-to-advisor advice-seeking behaviors using social network analysis (SNA). SNA provides a valuable quantitative lens to map social structures and reveal potential collaborative opportunities and barriers. Method Cross-sectional surveys on advice-seeking behavior were collected from 95 medical students enrolled in the research program from 2016 to 2023. The data were obtained from medical students awarded research presentations and publication grants. SNA was used to visualize the dynamics of advice-seeking behaviors and research community structure. Path analysis and subgroup analysis were then conducted to identify influential success factors. Results SNA revealed a shift towards decentralized advice-seeking behaviors and a rising trend in peer-to-peer advice-seeking. Our analysis identified modularity or group formation as a key social mechanism that mediated the number of projects by 20.41% (p = 0.04). Students preferentially seek advice from those at a similar academic year and stage (preclinical vs. clinical), while gender and field of research interest did not show a significant impact. Subgroup analysis also revealed distinct variations in advice-seeking patterns among genders, academic stages, cohort statuses, and publication statuses. Discussion This study presents the first empirical exploration of advice-seeking dynamics within the undergraduate research community. Based on the network perspective, this study identifies group formation as a mediator toward research productivity that medical educators should consider. Moreover, studying advice-seeking behavior can unveil the influences of institutional policy and the hidden factors affecting undergraduate collaboration patterns. Encouraging research diversity and establishing a student research mentorship program can potentially promote research productivity and desirable outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Exploring Advice-Seeking Dynamics in Undergraduate Medical Research: A Social Network Analysis

Jarukasemkit,

Yoadsanit,

Teansue

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Social networks in humans and other organisms can emerge and change through time in ways that might be related to SAI ( Hobson et al, 2013 ; Hilbert et al, 2016 ). The de novo emergence of a social network is reported to involve dynamic formation and breakage of links ( Pomeroy et al, 2020 ; Xu et al, 2021 ). Online social networks have been proposed to display self-organizing criticality and the emergence of new functional properties ( Tadic et al, 2017 ; Tadic and Melnik, 2021 ).…”

Section: Sai At Other Levels Of Biological Organizationmentioning

confidence: 99%

Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging

Tower

2024

Front. Aging

View full text Add to dashboard Cite

Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.

show abstract