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Social and Behavioral Sciences Commons

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University of Wisconsin Milwaukee

International Journal of Geospatial and Environmental Research

Keyword Network Analysis

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Full-Text Articles in Social and Behavioral Sciences

What Geographers Research: An Analysis Of Geography Topics, Clusters, And Trends Using A Keyword Network Analysis Approach And The 2000-2019 Aag Conference Presentations, Jeong C. Seong, Chul Sue Hwang, Ana Stanescu, Youngho Lee, Yubin Lee Feb 2022

What Geographers Research: An Analysis Of Geography Topics, Clusters, And Trends Using A Keyword Network Analysis Approach And The 2000-2019 Aag Conference Presentations, Jeong C. Seong, Chul Sue Hwang, Ana Stanescu, Youngho Lee, Yubin Lee

International Journal of Geospatial and Environmental Research

The spectrum of geographic research topics is very broad, and several thousands of research projects are presented at AAG annual conferences. This research aims at analyzing geography research topics, clusters, and trends using conference presentation data. We analyzed the 2000-2019 AAG conference presentations with keyword network analysis methods. The most frequently used keywords during the 20-year span were GIS, followed by Remote Sensing, Climate Change, Urban, China, Education, Political Ecology, Migration, Gender, and Agriculture. Results showed that geographic research has focused on six major clusters during 2000-2019: GIS, Urban, Climate Change, Political Ecology, People, and Education. About 68.6 percent of …


A Comparison Of Network Clustering Algorithms In Keyword Network Analysis: A Case Study With Geography Conference Presentations, Youngho Lee, Yubin Lee, Jeong Seong, Ana Stanescu, Chul Sue Hwang Jul 2020

A Comparison Of Network Clustering Algorithms In Keyword Network Analysis: A Case Study With Geography Conference Presentations, Youngho Lee, Yubin Lee, Jeong Seong, Ana Stanescu, Chul Sue Hwang

International Journal of Geospatial and Environmental Research

The keyword network analysis has been used for summarizing research trends, and network clustering algorithms play important roles in identifying major research themes. In this paper, we performed a comparative analysis of network clustering algorithms to find out their performances, effectiveness, and impact on cluster themes. The AAG (American Association for Geographers) conference datasets were used in this research. We evaluated seven algorithms with modularity, processing time, and cluster members. The Louvain algorithm showed the best performance in terms of modularity and processing time, followed by the Fast Greedy algorithm. Examining cluster members also showed very coherent connections among cluster …