Graduate Student Profiles

Wei Luo

Wei LuoWei Luo, who will graduate from Penn State with Ph.D in Geography in August 2014, has accepted a post-doc position in the School of Computing, Informatics & Decision Systems Engineering at Arizona State University. He will work on an NGA-funded project to address the national security risks of climate change.  

As a graduate affiliate of the GeoVISTA Center, Wei contributed to several projects, including SensePlace2, STempo, and the Vaccine Modeling Initiative. He also developed, as part of his thesis research, the GeoSocialApp, a visualization tool that supports the exploration of spatial-social networks among network, geographical, and attribute spaces. Using mixed methods - computational and visual, the GeoSocialApp enables discovery of complex patterns in large spatial-social network datasets in an effective and efficient way. Wei successfully defended his thesis, Geovisual Analytics Approaches for the Integration of Geography and Social Network Contexts, in July of 2014.

More About Wei's Research

RemotelySpatial analysis and social network analysis typically consider social processes in their own specific contexts, either geographical or network space. Both approaches demonstrate strong conceptual overlaps. For example, actors close to each other tend to have greater similarity than those far apart; this phenomenon has different labels in geography (spatial autocorrelation) and in network science (homophily). In spite of those conceptual and observed overlaps, the integration of geography and social network context has not received the attention needed in order to develop a comprehensive understanding of their interaction or their impact on outcomes of interest, such as population health behaviors, information dissemination, or human behavior in a crisis.
In order to address this gap, Wei’s dissertation discusses the integration of geographic with social network perspectives applied to understanding social processes in place at both theoretical and methodological levels. At the theoretical level, this dissertation develops a theoretical framework to integrate geographical context, network context, and societal context (e.g., political or economic background) to understand the geo-social interaction in certain societal contexts. The framework extends the concepts of nearness and relationship in terms of the First Law of Geography as a matter of both geographical and social network distance, relationship, and interaction. At the methodological level, the integration of geography and social network contexts is framed within a new interdisciplinary field: visual analytics, in which three major application-oriented subfields (data exploration, decision-making, and predictive analysis) are used to organize discussion. In each subfield, this dissertation presents a theoretical framework first, and then reviews what has been achieved regarding geo-social visual analytics in order to identify potential future research.
This dissertation also develops two novel geo-social visual analytics tools to study the complex interaction between spatial and social relationships at different geographical levels: the regional level (e.g., country, state, or county) and the individual level (e.g., person, or organization). The first tool, called GeoSocialApp, uses data for international trade networks among different countries to empirically study the interaction of spatial-social relationships across geographical regions at multiple levels of network hierarchy. The second tool, GS-EpiViz, takes network statistics relevant to air-borne disease transmission and control and integrates them into appropriate visualization techniques, thereby facilitating the exploration of human interaction network structures to design advanced disease control strategies. This tool also implements agent-based epidemic models to test and evaluate control strategies in a highly interactive and iterative manner. The two tools provide generic frameworks to explore spatial-social relationships at geographical scales, ranging from individual-level to national-level.

The research reported here opens a new research area: geo-social visual analytics and achieves a substantial step forward regarding the science and technology of this area. However, there is much more research that needs to be done. In the meantime, the insights generated in this research provide an initial foundation for the future scientific research and technological challenges on geo-social visual analytics.

Papers resulting from Wei’s research:
Luo W, MacEachren AM. (2014) Geo-Social Visual Analytics. Journal of Spatial Information Science. 8: 27-66.

Luo W, Yin PF, Di Q, Hardisty F, and MacEachren AM. (2014) A Geovisual Analytic Approach to Understanding Spatial-Social Relationships in the International Trade Network. PLoS ONE 9(2): e88666.

Luo W, MacEachren AM, Yin PF, and Hardisty F, 2012. GeoSocialApp: A Visual Exploratory Data Analysis Tool for Spatial-Social Network. CyberGIS'12 Poster Exhibition. Champaign, IL: August 7, 2012.

Related Posters:

Wei’s full thesis: Geovisual Analytics Approaches for the Integration of Geography and Social Network Contexts

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