WK 15 - Unstructured and Qualitative Data on Socio-Ecological Systems

Sunday, August 6, 2017: 8:00 AM-11:30 AM
A106, Oregon Convention Center
Ian T. Carroll, National Socio-Environmental Synthesis Center
Morey Burnham, Idaho State University
Discovery at the interface of human and ecological systems increasingly requires researchers to knit inference from unstructured and qualitative data with traditional methods in ecology. Data derived from print and social media, interviews, and other instruments pioneered by social scientists can yield knowledge about the motivations and decisions of human agents (individuals, corporations or governments) that interact with ecological systems. The National Socio-Environmental Synthesis Center (SESYNC) helps researchers from many different disciplines efficiently use cyberinfrastructure to process, combine and analyze all types of data in support of the Center's mission.

This workshop introduces participants to techniques for processing unstructured data and discovering relationships among qualitative variables. Through hands-on exercises, participants will implement an example workflow that begins with capturing textual data from a web-based application program interface (API), includes options for content analysis of the acquired data, and ends by identifying associations within the qualitative data derived from content analysis. Specific topics include web API requests, regular expressions, topic modeling, text analysis, network models, and computer assisted thematic coding. The aim is to demonstrate to researchers familiar with the collection and analysis of quantitative data an analogous workflow centered on non-numerical data types, expanding the potential scope of synthetic research on socio-ecological systems.

The anticipated audience includes ecologists engaged in interdisciplinary research who want to better understand qualitative data analysis, as well as researchers with training in social sciences hoping to expand their capacity to utilize unstructured and qualitative data.

Registration Fee: $25

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