All Issue

2022 Vol.56, Issue 3 Preview Page
A Picture of Geography Revealed by a Keyword Network Analysis of the 2020 AAG Conference

2020년 AAG 학회 키워드 네트워크 분석을 통한 지리학 연구 동향 분석

Stanescu Anaa
,
Jeong Chang Seongb
,
Yubin Leec
,
Chul Sue Hwangd*
애나 스타네스쿠a
,
성 정창b
,
이 유빈c
,
황 철수d*
aAssociate Professor, University of West Georgia
bProfessor, University of West Georgia
cGraduate Student, Department of Geography, Kyung Hee University
dProfessor, Department of Geography, Kyung Hee University
a웨스트 조지아 대학 부교수
b웨스트 조지아 대학 교수
c경희대학교 지리학과 대학원생
d경희대학교 지리학과 교수
*Corresponding Author
30 September 2022. pp. 177-187
PDF XML Citation
Abstract

Every year, thousands of research findings are presented at the American Association of Geographers (AAG) conference, making it difficult for scholars to quickly identify the meeting's major topics and themes. The goal of this study is to provide a picture of geography through the lens of the 2020 AAG meeting. We summarized the conference presentations using a keyword network analysis (KNA) approach by computing several established metrics, such as various centrality indicators, neighborhood connectivity, and distribution of node degrees. We found “urban” to be the most frequently occurring keyword as well as the most influential topic, and “urban - planning” the most common co-occurrence of terms. “GIS” (Geographic Information Systems) and “spatial data science” are autonomous themes and the former appears to be less influential than the latter at this edition of AAG. The keyword network also exhibits the “small-world” property, which can potentially anticipate future research directions.

Keywords
keyword network analysis
geography
geographic research
geography clusters
research trends
AAG conference

매년 수천 개의 연구가 미국 지리학 학회(AAG)에서 발표되기 때문에 연구자들은 학회의 주요 관심과 주제를 신속하게 인지하기 어렵다. 본 연구의 목표는 2020년 AAG 학회에 제출된 초록을 통해 지리학 연구에 대한 전반적인 동향을 분석하는 것이다. 본 연구에서는 키워드 네트워크 분석(KNA) 방법론을 활용하였으며, 이를 바탕으로 다양한 중심성 지표, 이웃 연결성, 노드 차수 분포 등을 도출하였다. 그 결과, ‘urban'이 가장 자주 등장하는 키워드이자 가장 영향력 있는 주제로 나타났고, ‘urban'과 ’planning'이 가장 연관성이 높은 키워드로 분석되었다. 또, ‘GIS'와 ‘spatial data science'는 독립적으로 기재되었으며, 해당 AAG 학회에서는 ‘spatial data science'가 ‘GIS'보다 영향력이 높은 것으로 드러났다. 키워드 네트워크 분석을 통해, 잠재적으로 미래 연구 주제를 예측할 수 있는 ‘small-world' 특징이 있다는 것도 확인할 수 있었다.

키워드
키워드 네트워크 분석
지리학
지리학 연구
지리학 클러스터
연구 동향
AAG 학회
References
1
Backstrom, L., P. Boldi, M. Rosa, J. Ugander, and S. Vigna, 2012, Four degrees of separation. In Proceedings of the 4th Annual ACM Web Science Conference 33-42. 10.1145/2380718.2380723
2
Blondel, V. D., J. L. Guillaume, R. Lambiotte, and E. Lefebvre, 2008, Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008(10): 10008. 10.1088/1742-5468/2008/10/P10008
3
Choi, J. and Y. S. Hwang, 2014, Patent keyword network analysis for improving technology development efficiency. Technological Forecasting and Social Change 83: 170-182. 10.1016/j.techfore.2013.07.004
4
Choi, J., S. Yi, and K.C. Lee, 2011, Analysis of keyword networks in MIS research and implications for predicting knowledge evolution. Information & Management 48(8): 371-381. 10.1016/j.im.2011.09.004
5
Curtin, K.M., 2007, Network analysis in geographic information science: Review, assessment, and projections. Cartography and Geographic Information Science 34(2): 103-111. 10.1559/152304007781002163
6
De la Pena Sarracen, G.L. and P. Rosso, 2018, Automatic text summarization based on betweenness centrality. In Proceedings of the 5th Spanish Conference on Information Retrieval 1-4. 10.1145/3230599.3230611
7
Erdos, P. and A. Renyi, 1960, On the evolution of random graphs. The Mathematical Institute of the Hungarian Academy of Sciences 5(1): 17-60.
8
Franceschet, M., 2011, Collaboration in computer science: A network science approach. Journal of the American Society for Information Science and Technology 62(10): 1992-2012. 10.1002/asi.21614
9
Freeman, L.C., 1978, Centrality in social networks conceptual clarification. Social Networks 1(3): 215-239. 10.1016/0378-8733(78)90021-7
10
Kim, T., D. Lee, H. Lim, U.K. Lee, H. Cho, and K. Cho, 2021, Exploring research trends and network characteristics in construction automation and robotics based on keyword network analysis. Journal of Asian Architecture and Building Engineering 20(4): 442-457. 10.1080/13467581.2020.1798774
11
Lee, Y., Y. Lee, J. Seong, A. Stanescu, and C.S. Hwang, 2020, A comparison of network clustering algorithms in keyword network analysis: A case study with geography conference presentations. International Journal of Geospatial and Environmental Research 7(3): 1-14.
12
Lee, Y., Y. Lee, J. Seong, T. Hwang, and C.S. Hwang, 2019, Analysis of GIS research trends in the US with AAG conference presentations from 2000-2019. The Geographical Journal of Korea 53(4): 495-508.
13
Matusiak, A. and M. Morzy, 2012, Social network analysis in scientometrics. In 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems 692-699. 10.1109/SITIS.2012.105
14
Melo, A.V.F.D. and A.P.D. Queiroz, 2019, Bibliometric mapping of papers on geographical information systems (2007-2016). Boletim de Ciencias Geodesicas 25(3): 1-16. 10.1590/s1982-21702019000300015
15
Newman, M.E., 2004, Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences 101: 5200-5205. 10.1073/pnas.030754510014745042PMC387296
16
Park, J. and E. Jeong, 2019, Service quality in tourism: A systematic literature review and keyword network analysis. Sustainability 11(13): 3665. 10.3390/su11133665
17
Park, J., T.Z. Fu, and D.M. Chiu, 2012, Networking, clustering and brokering keywords in the computer science research. In Seventh International Conference on Digital Information Management (ICDIM 2012) 110-115. 10.1109/ICDIM.2012.6360127
18
Seong, J.C., S. Ji, A. Stanescu, Y. Lee, and C.S. Hwang, What will be Presented at the 2021 AAG Meeting?, AAG Newletters April 2021. 10.14433/2017.0088
19
Sun, Y., R. Barber, M. Gupta, C.C. Aggarwal, and J. Han, 2011, Co-author relationship prediction in heterogeneous bibliographic networks. In 2011 International Conference on Advances in Social Networks Analysis and Mining 121-128. 10.1109/ASONAM.2011.112
20
Zhu, D., D. Wang, S.U. Hassan, and P. Haddawy, 2013, Small-world phenomenon of keywords network based on complex network. Scientometrics 97(2): 435-442. 10.1007/s11192-013-1019-3
21
Zhu, S., W. Jin, and C. He, 2019. On evolutionary economic geography: A literature review using bibliometric analysis. European Planning Studies 27(4): 639-660. 10.1080/09654313.2019.1568395
Information
  • Publisher :The Korean Association of Professional Geographers
  • Publisher(Ko) :국토지리학회
  • Journal Title :국토지리학회지
  • Journal Title(Ko) :THE GEOGRAPHICAL JOURNAL OF KOREA
  • Volume : 56
  • No :3
  • Pages :177-187
  • Received Date : 2022-09-03
  • Accepted Date : 2022-09-08
  • DOI :https://doi.org/10.22905/kaopqj.2022.56.3.3
Journal Informaiton 국토지리학회지 국토지리학회지
Online Submission
  • NRF
  • KISTI Current Status
  • KISTI Cited-by
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close