FN Thomson Reuters Web of Knowledge
VR 1.0
PT J
AU Chen, CM
   Hu, ZG
   Liu, SB
   Tseng, H
AF Chen, Chaomei
   Hu, Zhigang
   Liu, Shengbo
   Tseng, Hung
TI Emerging trends in regenerative medicine: a scientometric analysis in
   CiteSpace
SO EXPERT OPINION ON BIOLOGICAL THERAPY
LA English
DT Review
DE CiteSpace; co-citation analysis; induced pluripotent stem cells;
   regenerative medicine; scientometrics
ID PLURIPOTENT STEM-CELLS; REPROGRAMMING FACTORS; SCIENTIFIC LITERATURE;
   HUMAN FIBROBLASTS; DEFINED FACTORS; RESEARCH FRONTS; GENERATION; MOUSE;
   STATE; PATIENT
AB Introduction: Regenerative medicine involves research in a number of fields and disciplines such as stem cell research, tissue engineering and biological therapy in general. As research in these areas advances rapidly, it is critical to keep abreast of emerging trends and critical turns of the development of the collective knowledge.
   Areas covered: A progressively synthesized network is derived from 35,963 original research and review articles that cite 3875 articles obtained from an initial topic search on regenerative medicine between 2000 and 2011. CiteSpace is used to facilitate the analysis of the intellectual structure and emerging trends.
   Expert opinion: A major ongoing research trend is concerned with finding alternative reprogramming techniques as well as refining existing ones for induced pluripotent stem cells (iPSCs). A more recent emerging trend focuses on the structural and functional equivalence between iPSCs and human embryonic stem cells and potential clinical and therapeutic implications on regenerative medicine in a long run. The two trends overlap in terms of what they cite, but they are distinct and have different implications on future research. Visual analytics of the literature provides a valuable, timely, repeatable and flexible approach in addition to traditional systematic reviews so as to track the development of new emerging trends and identify critical evidence.
C1 Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
   Dalian Univ Technol, WISELAB, Dalian, Peoples R China.
   NIAMSD, NIH, Div Skin & Rheumat Dis, Bethesda, MD 20892 USA.
RP Chen, CM (reprint author), Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut St, Philadelphia, PA 19104 USA.
EM chaomei.chen@drexel.edu
RI Chen, Chaomei/A-1252-2007
OI Chen, Chaomei/0000-0001-8584-1041
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2010, J AM SOC INF SCI TEC, V61, P1386, DOI 10.1002/asi.21309
   Chen CM, 2004, P NATL ACAD SCI USA, V101, P5303, DOI 10.1073/pnas.0307513100
   Chen CM, 2012, J AM SOC INF SCI TEC, V63, P431, DOI 10.1002/asi.21694
NR 62
TC 1
Z9 1
PU INFORMA HEALTHCARE
PI LONDON
PA TELEPHONE HOUSE, 69-77 PAUL STREET, LONDON EC2A 4LQ, ENGLAND
SN 1471-2598
J9 EXPERT OPIN BIOL TH
JI Expert Opin. Biol. Ther.
PD MAY
PY 2012
VL 12
IS 5
BP 593
EP 608
DI 10.1517/14712598.2012.674507
PG 16
WC Biotechnology & Applied Microbiology; Medicine, Research & Experimental
SC Biotechnology & Applied Microbiology; Research & Experimental Medicine
GA 936ZA
UT WOS:000303627600009
ER

PT J
AU Liu, SB
   Chen, CM
AF Liu, Shengbo
   Chen, Chaomei
TI The proximity of co-citation
SO SCIENTOMETRICS
LA English
DT Article; Proceedings Paper
CT 13th International Conference on Scientometrics and Informetrics
CY JUL 04-07, 2011
CL Durban, SOUTH AFRICA
SP Int Soc Scientometr & Informetr (ISSI), Durban Univ Technol
HO Univ Zululand
DE Co-citation proximity; Co-citation analysis; Citation contextual; PubMed
   Central
ID SCIENTIFIC LITERATURE; INDEX
AB Traditional co-citation analysis has not taken the proximity of co-cited references into account. As long as two references are cited by the same article, they are retreated equally regardless the distance between where citations appear in the article. Little is known about what additional insights into citation and co-citation behaviours one might gain from studying distributions of co-citation in terms of such proximity. How are citations distributed in an article? What insights does the proximity of co-citation provide? In this article, the proximity of a pair of co-cited reference is defined as the nearest instance of the co-citation relation in text. We investigate the proximity of co-citation in full text of scientific publications at four levels, namely, the sentence level, the paragraph level, the section level, and the article level. We conducted four studies of co-citation patterns in the full text of articles published in 22 open access journals from BioMed Central. First, we compared the distributions of co-citation instances at four proximity levels in journal articles to the traditional article-level co-citation counts. Second, we studied the distributions of co-citations of various proximities across organizational sections in articles. Third, the distribution of co-citation proximity in different co-citation frequency groups is investigated. Fourth, we identified the occurrences of co-citations at different proximity levels with reference to the corresponding traditional co-citation network. The results show that (1) the majority of co-citations are loosely coupled at the article level, (2) a higher proportion of sentence-level co-citations is found in high co-citation frequencies than in low co-citation frequencies, (3) tightly coupled sentence-level co-citations not only preserve the essential structure of the corresponding traditional co-citation network but also form a much smaller subset of the entire co-citation instances typically considered by traditional co-citation analysis. Implications for improving our understanding of underlying factors concerning co-citations and developing more efficient co-citation analysis methods are discussed.
C1 Dalian Univ Technol, WISE Lab, Dalian, Peoples R China.
   Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
RP Liu, SB (reprint author), Dalian Univ Technol, WISE Lab, Dalian, Peoples R China.
EM liushengbo1121@gmail.com; chaomei.chen@drexel.edu
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2004, P NATL ACAD SCI USA, V101, P5303, DOI 10.1073/pnas.0307513100
NR 23
TC 0
Z9 0
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0138-9130
J9 SCIENTOMETRICS
JI Scientometrics
PD MAY
PY 2012
VL 91
IS 2
BP 495
EP 511
DI 10.1007/s11192-011-0575-7
PG 17
WC Computer Science, Interdisciplinary Applications; Information Science &
   Library Science
SC Computer Science; Information Science & Library Science
GA 921LD
UT WOS:000302478200014
ER

PT J
AU Chen, CM
AF Chen, Chaomei
TI Predictive Effects of Structural Variation on Citation Counts
SO JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY
LA English
DT Article
ID UNDISCOVERED PUBLIC KNOWLEDGE; NETWORKS; SCIENCE; FORESIGHT; ARTICLES;
   PERSPECTIVE; TECHNOLOGY; PSYCHOLOGY; DYNAMICS; PATTERNS
AB A critical part of a scientific activity is to discern how a new idea is related to what we know and what may become possible. As the number of new scientific publications arrives at a rate that rapidly outpaces our capacity of reading, analyzing, and synthesizing scientific knowledge, we need to augment ourselves with information that can effectively guide us through the rapidly growing intellectual space. In this article, we address a fundamental issue concerning what kinds of information may serve as early signs of potentially valuable ideas. In particular, we are interested in information that is routinely available and derivable upon the publication of a scientific paper without assuming the availability of additional information such as its usage and citations. We propose a theoretical and computational model that predicts the potential of a scientific publication in terms of the degree to which it alters the intellectual structure of the state of the art. The structural variation approach focuses on the novel boundary-spanning connections introduced by a new article to the intellectual space. We validate the role of boundary-spanning in predicting future citations using three metrics of structural variation-namely, modularity change rate, cluster linkage, and Centrality Divergence-along with more commonly studied predictors of citations such as the number of coauthors, the number of cited references, and the number of pages. Main effects of these factors are estimated for five cases using zero-inflated negative binomial regression models of citation counts. Key findings indicate that (a) structural variations measured by cluster linkage are a better predictor of citation counts than are the more commonly studied variables such as the number of references cited, (b) the number of coauthors and the number of references are both good predictors of global citation counts to a lesser extent, and (c) the Centrality Divergence metric is potentially valuable for detecting boundary-spanning activities at interdisciplinary levels. The structural variation approach offers a new way to monitor and discern the potential of newly published papers in context. The boundary-spanning mechanism offers a conceptually simplified and unifying explanation of the roles played by commonly studied extrinsic properties of a publication in the study of citation behavior.
C1 Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
RP Chen, CM (reprint author), Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut St, Philadelphia, PA 19104 USA.
EM chaomei.chen@drexel.edu
RI Chen, Chaomei/A-1252-2007
OI Chen, Chaomei/0000-0001-8584-1041
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2010, J AM SOC INF SCI TEC, V61, P1386, DOI 10.1002/asi.21309
   Chen CM, 2002, J AM SOC INF SCI TEC, V53, P678, DOI 10.1002/asi.10075
NR 55
TC 2
Z9 2
PU WILEY-BLACKWELL
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1532-2882
J9 J AM SOC INF SCI TEC
JI J. Am. Soc. Inf. Sci. Technol.
PD MAR
PY 2012
VL 63
IS 3
BP 431
EP 449
DI 10.1002/asi.21694
PG 19
WC Computer Science, Information Systems; Information Science & Library
   Science
SC Computer Science; Information Science & Library Science
GA 902KZ
UT WOS:000301038300001
ER

PT J
AU Chen, CM
   Ibekwe-SanJuan, F
   Hou, JH
AF Chen, Chaomei
   Ibekwe-SanJuan, Fidelia
   Hou, Jianhua
TI The Structure and Dynamics of Cocitation Clusters: A
   Multiple-Perspective Cocitation Analysis
SO JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY
LA English
DT Article
ID INFORMATION-SCIENCE; RESEARCH FRONTS; COMBINING BIBLIOMETRICS;
   SCIENTIFIC LITERATURE; RELEVANCE THEORY; CONCEPT SYMBOLS; GOOGLE
   SCHOLAR; KNOWLEDGE; NETWORKS; WEB
AB A multiple-perspective cocitation analysis method is introduced for characterizing and interpreting the structure and dynamics of cocitation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Cocitation networks are decomposed into cocitation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a cocitation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of information science as defined by 12 journals published between 1996 and 2008: (a) a comparative author cocitation analysis (ACA), (b) a progressive ACA of a time series of cocitation networks, and (c) a progressive document cocitation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.
C1 Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
   Univ Lyon 3, ELICO, F-69008 Lyon, France.
   Dalian Univ Technol, WISELAB, Dalian, Peoples R China.
RP Chen, CM (reprint author), Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut St, Philadelphia, PA 19104 USA.
EM chaomei.chen@drexel.edu; fidelia.ibekwe-sanjuan@univ-lyon3.fr;
   hqzhixing@gmail.com
RI Chen, Chaomei/A-1252-2007
OI Chen, Chaomei/0000-0001-8584-1041
FU National Science Foundation [IIS-0612129]
FX This work is supported in part by the National Science Foundation under
   grant IIS-0612129. We wish to thank Eric SanJuan of the University of
   Avignon, France, for implementing the Enertex sentence ranking algorithm
   used in this study; Howard White, Drexel University, for his detailed
   and constructive comments on an earlier draft; Dangzhi Zhao and Andreas
   Strotmann of the University of Alberta, Canada, for providing detailed
   factor loading results of their factor analysis for the comparative ACA
   and for their comments on an earlier draft of the article; and anonymous
   reviewers for their detailed reviews. Special thanks to Zeyuan Liu and
   members of the WISELAB at Dalian University of Technology, China, for
   their valuable feedback based on their extensive use of earlier versions
   of CiteSpace.
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2004, P NATL ACAD SCI USA, V101, P5303, DOI 10.1073/pnas.0307513100
NR 74
TC 30
Z9 33
PU JOHN WILEY & SONS INC
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN, NJ 07030 USA
SN 1532-2882
J9 J AM SOC INF SCI TEC
JI J. Am. Soc. Inf. Sci. Technol.
PD JUL
PY 2010
VL 61
IS 7
BP 1386
EP 1409
DI 10.1002/asi.21309
PG 24
WC Computer Science, Information Systems; Information Science & Library
   Science
SC Computer Science; Information Science & Library Science
GA 615QV
UT WOS:000279151600007
ER

PT J
AU Gao, JP
   Ding, K
   Teng, L
   Pang, J
AF Gao, Ji-ping
   Ding, Kun
   Teng, Li
   Pang, Jie
TI Hybrid documents co-citation analysis: making sense of the interaction
   between science and technology in technology diffusion
SO SCIENTOMETRICS
LA English
DT Article
DE Hybrid documents co-citation; Technology diffusion; Cluster analysis;
   Network analysis
ID SCIENTIFIC LITERATURE; NANOTECHNOLOGY; LITERATURES; PERSPECTIVE;
   INDICATORS; PATTERNS; BUSINESS; PATENTS; LINKAGE; TRENDS
AB The paper presents a methodology called hybrid documents co-citation analysis, for studying the interaction between science and technology in technology diffusion. Our approach rests mostly on patent citation, cluster analysis and network analysis. More specifically, with the patents citing Smalley RE in Derwent innovations index as the data sets, the paper implemented hybrid documents co-citation network through two procedures. Then spectrum cluster algorithm was used to reveal the knowledge structure in technology diffusion. After that, with the concordance between network properties and technology diffusion mechanisms, three indicators containing degree, betweenness and citation half-life, were calculated to discuss the basic documents in the pivotal position during the technology diffusion. At last, the paper summarized the hybrid documents co-citation analysis in practise, thus concluded that science and technology undertook different functions and acted dominatingly in the different period of technology diffusion, though they were co-activity all the time.
C1 Dalian Univ Technol, Inst Sci Studies & S&T Management, Dalian, Liaoning, Peoples R China.
   Dalian Univ Technol, WISE Lab, Dalian, Liaoning, Peoples R China.
RP Gao, JP (reprint author), Dalian Univ Technol, Inst Sci Studies & S&T Management, 2 Linggong Rd, Dalian, Liaoning, Peoples R China.
EM tulipgao@mail.dlut.edu.cn
FU National Social Science Foundation of China [08BTQ025]; Specialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   [20110041110034]
FX This paper was initiated at the 13th ISSI Conference, Duban, South
   Africa. The authors would like to thank the anonymous referees for their
   helpful comments. And the authors also like to acknowledge the financial
   support from the National Social Science Foundation of China (Project
   No.08BTQ025) and Specialized Research Fund for the Doctoral Program of
   Higher Education (SRFDP) (20110041110034).
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2010, J AM SOC INF SCI TEC, V61, P1386, DOI 10.1002/asi.21309
   Chen CM, 2004, P NATL ACAD SCI USA, V101, P5303, DOI 10.1073/pnas.0307513100
NR 28
TC 0
Z9 0
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0138-9130
J9 SCIENTOMETRICS
JI Scientometrics
PD NOV
PY 2012
VL 93
IS 2
BP 459
EP 471
DI 10.1007/s11192-012-0691-z
PG 13
WC Computer Science, Interdisciplinary Applications; Information Science &
   Library Science
SC Computer Science; Information Science & Library Science
GA 025XL
UT WOS:000310230400014
ER

PT J
AU Niazi, M
   Hussain, A
AF Niazi, Muaz
   Hussain, Amir
TI Agent-based computing from multi-agent systems to agent-based models: a
   visual survey
SO SCIENTOMETRICS
LA English
DT Article
DE Scientometrics; Visualization; Agent-based modeling; Multiagent systems;
   Individual-based modeling; CiteSpace
ID SCIENTIFIC LITERATURES; INTELLECTUAL STRUCTURE; AUTHOR COCITATION;
   TRIPLE-HELIX; SCIENCE; SCIENTOMETRICS; INNOVATION; KNOWLEDGE; DYNAMICS;
   CITATION
AB Agent-based computing is a diverse research domain concerned with the building of intelligent software based on the concept of "agents". In this paper, we use Scientometric analysis to analyze all sub-domains of agent-based computing. Our data consists of 1,064 journal articles indexed in the ISI web of knowledge published during a 20 year period: 1990-2010. These were retrieved using a topic search with various keywords commonly used in sub-domains of agent-based computing. In our proposed approach, we have employed a combination of two applications for analysis, namely Network Workbench and CiteSpace-wherein Network Workbench allowed for the analysis of complex network aspects of the domain, detailed visualization-based analysis of the bibliographic data was performed using CiteSpace. Our results include the identification of the largest cluster based on keywords, the timeline of publication of index terms, the core journals and key subject categories. We also identify the core authors, top countries of origin of the manuscripts along with core research institutes. Finally, our results have interestingly revealed the strong presence of agent-based computing in a number of non-computing related scientific domains including Life Sciences, Ecological Sciences and Social Sciences.
C1 COMSATS Inst IT, Dept Biosci, Islamabad, Pakistan.
   Univ Stirling, Sch Nat Sci, Inst Comp Sci & Math, Stirling FK9 4LA, Scotland.
RP Niazi, M (reprint author), COMSATS Inst IT, Dept Biosci, Islamabad, Pakistan.
EM man@cs.stir.ac.uk; ahu@cs.stir.ac.uk
CR Chen CM, 2006, J AM SOC INF SCI TEC, V57, P359, DOI 10.1002/asi.20317
   Chen CM, 2001, J AM SOC INF SCI TEC, V52, P315, DOI 10.1002/1532-2890(2000)9999:9999<::AID-ASI1074>3.3.CO;2-U
NR 55
TC 4
Z9 4
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0138-9130
J9 SCIENTOMETRICS
JI Scientometrics
PD NOV
PY 2011
VL 89
IS 2
BP 479
EP 499
DI 10.1007/s11192-011-0468-9
PG 21
WC Computer Science, Interdisciplinary Applications; Information Science &
   Library Science
SC Computer Science; Information Science & Library Science
GA 840WU
UT WOS:000296473400002
ER

EF