{"id":15088,"date":"2019-10-14T10:05:26","date_gmt":"2019-10-14T14:05:26","guid":{"rendered":"https:\/\/www.samsi.info\/?page_id=15088"},"modified":"2021-04-29T16:17:34","modified_gmt":"2021-04-29T20:17:34","slug":"program-on-data-science-in-the-social-and-behavioral-sciences","status":"publish","type":"page","link":"https:\/\/www.samsi.info\/programs-and-activities\/semester-long-programs\/program-on-data-science-in-the-social-and-behavioral-sciences\/","title":{"rendered":"Program on Data Science in the Social and Behavioral Sciences"},"content":{"rendered":"

The Statistical and Applied Mathematical Sciences Institute (SAMSI) sponsored by the National Science Foundation (NSF) is hosting a semester-long program on Data Science in the Social and Behavioral Sciences <\/em>from January to May 2021. The program will be hosted at the University of North Carolina at Chapel Hill along with SAMSI\u2019s other partners at Duke University and North Carolina State University.<\/p>\n

The main component of the SAMSI Programs are several working groups that run throughout the semester.\u00a0 These working groups are bookended by an opening workshop (several days in January) and closing workshop (several days in April\/May).\u00a0\u00a0 The opening workshop will help set the directions of the semester-long working groups.<\/p>\n

The major themes of the SAMSI Data Science in the Social and Behavioral Sciences <\/em>program will include:<\/p>\n

    \n
  1. Social network analysis and network neuroscience, including challenges around network sampling, temporal and multilayer networks, and network modeling of disease and behavior.<\/li>\n
  2. Comparisons and synthesis in causal inference and statistical modeling across structural equation models, directed acyclic graphs, and counterfactual approaches.<\/li>\n
  3. Consideration of new forms of digital data and the methods to analyze such data. Possible examples include wearables, GPS tracking, web scraping, sensor data, computer-aided text analysis, sentiment analysis, intensive time-series, etc.<\/li>\n<\/ol>\n

    Program Working Groups<\/h2>\n

    Working Group I<\/strong><\/a>: Big Data Quality
    \nLeaders \u2013     Sunshine Hillygus<\/a> (Duke Political Science and Public Policy), Alex Volfovsky<\/a> ( Duke Statistics), SAMSI RA: Karen Medlin<\/a> (UNC Math)<\/p>\n

    Working Group II<\/strong><\/a>: Misinformation, Information Campaigns, and Event Data
    \nLeaders \u2013     Yijyun Lin<\/a> (University of Nevada, Reno), Ali H\u00fcrriyeto\u011flu<\/a>,\u00a0Ko\u00e7 University, <\/span>Ahmed M. Elmisery<\/a>, Malm University<\/p>\n

    Working Group III<\/strong><\/a>: Diffusion of Information in Online Social Networks
    \nLeader \u2013     Diego Fregolente<\/a>, SAMSI<\/p>\n

    Working Group IV<\/a><\/strong>: Simulated-data Experimentation to Understand
    \nLeader –     Keith O\u2019Rourke<\/a>, O’Rourke Consulting<\/p>\n

    Working Group V<\/a><\/strong>: Integrating and Expanding Networks of Networks Theories
    \nLeader –     Kate Albrecht<\/a>, University of Illinois-Chicago<\/p>\n

    Working Group VI<\/a><\/strong>: Spacial Mediation and Longitudinal Modeling
    \nLeader –     Emil Coman<\/a>, University of Connecticut<\/p>\n

    Working Group VII<\/a><\/strong>: Estimation of Agent-Based Models
    \nLeader – Bruce Rogers<\/p>\n

    Working Group VIII<\/a><\/strong>: Cross-Translating Contemporary Causal Modeling Methods
    \nLeaders –     Ken Bollen<\/a>, UNC & Emil Coman<\/a>, University of Connecticut<\/p>\n

    Working Group IX<\/a><\/strong>: Weights in Data Analysis
    \nLeader –     Stas Kolenikov<\/a>, Abt Associates<\/p>\n

    Working Group X<\/a><\/strong>: Causal Inference with Network Structures
    \nLeader \u2013\u00a0    Weihua An<\/a>, Emory University<\/p>\n

    Working Group XI<\/a><\/strong>: Brain Networks
    \nLeaders \u2013     Maria Bagonis<\/a>, Alana Campbell<\/a>, UNC<\/p>\n

    Working Group XII<\/strong><\/a>: Networks and Victimization
    \nLeader \u2013     Bernard Coles IV<\/a>, SAMSI\/Duke<\/p>\n

    Working Group XIII<\/strong><\/a>: Networks and Psychology\u00a0 (REGISTER<\/a>)<\/strong>
    \nLeader \u2013\u00a0    Ruchira Datta<\/a>, Datta Enterprises LLC<\/p>\n

     <\/p>\n

    To see more information on research and other opportunities, visit the links below:
    \n    Participation in Workshops<\/a>
    \n    Participation in Working Groups<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

    The Statistical and Applied Mathematical Sciences Institute (SAMSI) sponsored by the National Science Foundation (NSF) is hosting a semester-long program on Data Science in the Social and Behavioral Sciences from January to May 2021. The program will be hosted at the University of North Carolina at Chapel Hill along with SAMSI\u2019s other partners at Duke […]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":12136,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15088"}],"collection":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/comments?post=15088"}],"version-history":[{"count":81,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15088\/revisions"}],"predecessor-version":[{"id":17522,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15088\/revisions\/17522"}],"up":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/12136"}],"wp:attachment":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/media?parent=15088"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}