التفاصيل البيبلوغرافية
| العنوان: |
Descriptive statistics and correlations. |
| المؤلفون: |
Ruqin Ren, Jia He |
| سنة النشر: |
2023 |
| مصطلحات موضوعية: |
Evolutionary Biology, Ecology, Developmental Biology, Science Policy, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, potential solution space, offers new avenues, level evolutionary outcomes, first study examines, suggesting content exploration, using network data, 11 content traits, level knowledge evolution, three network traits, cultural evolution theory, content traits, knowledge evolution, cultural evolution, network traits, recent theory, driven evolution, two studies, significant difference, possible explanation, dynamic nature, article explores, 910 artifacts, 163 weeks |
| الوصف: |
Network interpretation illuminates our understanding of the dynamic nature of cultural evolution. Guided by cultural evolution theory, this article explores how people collectively develop knowledge through knowledge collaboration network traits. Using network data from 910 artifacts (the WikiProject Aquarium Fishes articles) over 163 weeks, two studies were designed to understand how collaboration network traits drive population and artifact-level knowledge evolution. The first study examines the selection pressure imposed by10 network traits (against 11 content traits) on population-level evolutionary outcomes. While network traits are vital in identifying natural selection pressure, intriguingly, no significant difference was found between network traits and content traits, challenging a recent theory on network-driven evolution. The second study utilizes time series analysis to reveal that three network traits (embeddedness, connectivity, and redundancy) at a prior time predict future artifact development trajectory. This implies that people collectively explore various positions in a potential solution space, suggesting content exploration as a possible explanation of knowledge evolution. In summary, understanding the interplay between network traits and content exploration provides valuable insights into the mechanisms driving knowledge evolution and offers new avenues for future research. |
| نوع الوثيقة: |
dataset |
| اللغة: |
unknown |
| Relation: |
https://figshare.com/articles/dataset/Descriptive_statistics_and_correlations_/24561982 |
| DOI: |
10.1371/journal.pone.0291097.t004 |
| الاتاحة: |
https://doi.org/10.1371/journal.pone.0291097.t004
https://figshare.com/articles/dataset/Descriptive_statistics_and_correlations_/24561982 |
| Rights: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.32BD5629 |
| قاعدة البيانات: |
BASE |