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題名 Exploring emerging trends in agent-based modeling using bibliometric analysis and growing hierarchical self-organizing maps
作者 姜國輝
Chiang, Johannes K.;Szu, Wei Wen
Chiang, Johannes K.
貢獻者 資管系
關鍵詞 Emerging Technology; Agent-Based Modeling (ABM); Growing Hierarchical Self-Organizing
Map (GHSOM); Informetrics; Bibliometrics; Scientometrics
日期 2018-03
上傳時間 24-Jan-2019 12:11:28 (UTC+8)
摘要 Agent-based modeling (ABM) refers to the computer simulation of agents in a dynamic system. The
underlying problem of ABM was first theorized by John von Neumann in 1940. However, research did not
address this problem until the concept of ABM emerged in this decade. This study highlights emerging trends
in international literature related to ABM for articles in the Social Science Citation Index (SSCI) database
published since 1995. Because of the lack of a state-of-the-art method to identify emerging technologies, we
employed the bibliometric technique and a growing hierarchical self-organizing map (GHSOM) to explore the
emerging trend of ABM.Firstly, this paper reviews ABM methodology and state-of-the-art research methods, namely the bibliometric
technique and GHSOMs. Secondly, we explain the research data and method. The dataset used in this study
was derived from the SSCI database of the Web of Science. An empirical search command was used to
retrieve data related to ABM and then a bibliometric analysis was performed on the ingested data. The results
revealed that ABM does emerge and development related to ABM continued to expand. We then deployed the
application of the GHSOM to topic analysis in three phases: a data-preprocessing phase, -clustering phase,
and -interpreting phase. The results indicated that the common topics related to ABM are complexity theory,
the prisoner’s dilemma, altruism, land-use change, cellular automata and innovation diffusion etc. This paper
illustrates the potential of using GHSOM to explore the applications of emerging technologies. The study is
the first of its kind thus far.
關聯 Journal of Engineering Technology, Volume 6, Special Issue, pp.50-70
資料類型 article
dc.contributor 資管系
dc.creator (作者) 姜國輝
dc.creator (作者) Chiang, Johannes K.;Szu, Wei Wen
dc.creator (作者) Chiang, Johannes K.
dc.date (日期) 2018-03
dc.date.accessioned 24-Jan-2019 12:11:28 (UTC+8)-
dc.date.available 24-Jan-2019 12:11:28 (UTC+8)-
dc.date.issued (上傳時間) 24-Jan-2019 12:11:28 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/122158-
dc.description.abstract (摘要) Agent-based modeling (ABM) refers to the computer simulation of agents in a dynamic system. The
underlying problem of ABM was first theorized by John von Neumann in 1940. However, research did not
address this problem until the concept of ABM emerged in this decade. This study highlights emerging trends
in international literature related to ABM for articles in the Social Science Citation Index (SSCI) database
published since 1995. Because of the lack of a state-of-the-art method to identify emerging technologies, we
employed the bibliometric technique and a growing hierarchical self-organizing map (GHSOM) to explore the
emerging trend of ABM.Firstly, this paper reviews ABM methodology and state-of-the-art research methods, namely the bibliometric
technique and GHSOMs. Secondly, we explain the research data and method. The dataset used in this study
was derived from the SSCI database of the Web of Science. An empirical search command was used to
retrieve data related to ABM and then a bibliometric analysis was performed on the ingested data. The results
revealed that ABM does emerge and development related to ABM continued to expand. We then deployed the
application of the GHSOM to topic analysis in three phases: a data-preprocessing phase, -clustering phase,
and -interpreting phase. The results indicated that the common topics related to ABM are complexity theory,
the prisoner’s dilemma, altruism, land-use change, cellular automata and innovation diffusion etc. This paper
illustrates the potential of using GHSOM to explore the applications of emerging technologies. The study is
the first of its kind thus far.
dc.format.extent 488230 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Journal of Engineering Technology, Volume 6, Special Issue, pp.50-70
dc.subject (關鍵詞) Emerging Technology; Agent-Based Modeling (ABM); Growing Hierarchical Self-Organizing
Map (GHSOM); Informetrics; Bibliometrics; Scientometrics
dc.title (題名) Exploring emerging trends in agent-based modeling using bibliometric analysis and growing hierarchical self-organizing maps
dc.type (資料類型) article