Combining Ego-centric Network Analysis and Dynamic Citation Network Analysis to Topic Modeling for Characterizing Research Trends (자아 중심 네트워크 분석과 동적 인용 네트워크를 활용한 토픽모델링 기반 연구동향 분석에 관한 연구)

So-Young Yu (유소영)

doi:10.3743/KOSIM.2015.32.1.153

Combining Ego-centric Network Analysis and Dynamic Citation Network Analysis to Topic Modeling for Characterizing Research Trends

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2015, 32(1), pp.153~169
DOI : 10.3743/KOSIM.2015.32.1.153
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : February 24, 2015
Accepted : March 9, 2015
Published : March 30, 2015

So-Young Yu ¹

¹한남대학교

Accredited

ABSTRACT

The combined approach of using ego-centric network analysis and dynamic citation network analysis for refining the result of LDA-based topic modeling was suggested and examined in this study. Tow datasets were constructed by collecting Web of Science bibliographic records of White LED and topic modeling was performed by setting a different number of topics on each dataset. The multi-assigned top keywords of each topic were re-assigned to one specific topic by applying an ego-centric network analysis algorithm. It was found that the topical cohesion of the result of topic modeling with the number of topic corresponding to the lowest value of perplexity to the dataset extracted by SPLC network analysis was the strongest with the best values of internal clustering evaluation indices. Furthermore, it demonstrates the possibility of developing the suggested approach as a method of multi-faceted research trend detection.

KEYWORDS

Ego-centric network, SPLC, Topic Modeling, DBI, Index S

Citation status

* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

Combining Ego-centric Network Analysis and Dynamic Citation Network Analysis to Topic Modeling for Characterizing Research Trends

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* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

Combining Ego-centric Network Analysis and Dynamic Citation Network Analysis to Topic Modeling for Characterizing Research Trends

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.