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Development of a System to Collect Social Network Data from College Students for Future Studies in Health Behavior and Academic Performance.

机译:开发了一种收集大学生社交网络数据的系统,以用于未来的健康行为和学习成绩研究。

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摘要

Researchers study social networks to understand how individuals with similar behavior form clusters, and what causes them to do so. Universities are interested in learning more about influential factors of student behavior, including the impact that their social networks have on these behaviors. We have done foundational work to collect a dataset about UCSD student social network data gathered from Facebook and academic data from the UCSD Registrar. Once complete, the social network portion of this dataset will also be combined with datasets on health behaviors, potentially to build predictive models for depression, substance abuse, and other important conditions.
机译:研究人员研究社交网络以了解具有相似行为的个人如何形成集群,以及促使他们这样做的原因。大学有兴趣更多地了解学生行为的影响因素,包括其社交网络对这些行为的影响。我们已经完成了基础工作,以收集有关从Facebook收集的UCSD学生社交网络数据和UCSD注册服务商的学术数据的数据集。一旦完成,该数据集的社交网络部分还将与健康行为数据集结合,有可能为抑郁症,药物滥用和其他重要状况建立预测模型。

著录项

  • 作者

    Lah, Mike Myoungwhan.;

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Sociology Theory and Methods.;Computer Science.;Web Studies.;Health Sciences Public Health.
  • 学位 M.S.
  • 年度 2013
  • 页码 36 p.
  • 总页数 36
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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