Papers of possible interest to readers of the SIG-Metrics List (November 24, 2014)
Eugene Garfield
eugene.garfield at THOMSONREUTERS.COM
Mon Nov 24 14:24:21 EST 2014
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Title: Assessing obliteration by incorporation in a full-text database: JSTOR, Economics, and the concept of "bounded rationality"
Authors: McCain, K
Author Full Names: McCain, Katherine W.
Source: SCIENTOMETRICS, 101 (2):1445-1459; 10.1007/s11192-014-1237-3<http://dx.doi.org/10.1007/s11192-014-1237-3> NOV 2014
Language: English
Document Type: Article
Author Keywords: Obliteration by incorporation, Economics, Full-text databases, Citation-in-context analysis
KeyWords Plus: CUMULATIVE ADVANTAGE; CITATION ANALYSIS; SCIENCE; PUBLICATION; DOCUMENTS; JOURNALS; EPONYMY
Abstract: To evaluate the usefulness of a full-text database as a source for assessing obliteration by incorporation (OBI), 3,707 article records including the catchphrases "bounded rationality" and/or "boundedly rational" (connected with the work of H. A. Simon) in the article text were retrieved from JSTOR, a full-text database with broad disciplinary coverage. Two subsets were analyzed-a 10 % systematic sample of all records and a set of all articles in Economics journals (with the addition of the Journal of Economic Theory). A majority of articles in the 10 % sample came from Economics and Management journals, while Psychology was poorly represented. In the 10 % sample, based on the percentage of true implicit citations between 1992 and 2009 in the 80 % of records that had a catchphrase in the body of the article, rather than just in the reference list, annual OBI ranged from 0 to 70 % (mean 33 %) with no discernible trend. The Economics articles showed a narrower range of OBI-fluctuating around 40 % implicit citations over the same time period. In both data sets, a large proportion of indirect citations were to sources that themselves cited a relevant work by Simon. Over 90 % of the articles in both the 10 % sample and the economics journal set would not have been retrieved with a database record search because they lacked the catchphrase in the record fields.
Addresses: Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.
E-mail Addresses: mccainkw at drexel.edu
Cited Reference Count: 28
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900033
Cited References:
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Title: Comparative study on structure and correlation among author co-occurrence networks in bibliometrics
Authors: Qiu, JP; Dong, K; Yu, HQ
Author Full Names: Qiu, Jun-Ping; Dong, Ke; Yu, Hou-Qiang
Source: SCIENTOMETRICS, 101 (2):1345-1360; 10.1007/s11192-014-1315-6<http://dx.doi.org/10.1007/s11192-014-1315-6> NOV 2014
Language: English
Document Type: Article
Author Keywords: Co-authorship analysis, Author co-citation analysis, Author bibliographic coupling, Correlation analysis, Bibliometrics
KeyWords Plus: PEARSONS CORRELATION-COEFFICIENT; BIBLIOGRAPHIC-COUPLING ANALYSIS; INFORMATION-SCIENCE; COCITATION ANALYSIS; CO-AUTHORSHIP; SCIENTIFIC COLLABORATION; COAUTHORSHIP NETWORKS; INTELLECTUAL SPACE; ALL-AUTHOR; CITATION
Abstract: This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.
Addresses: [Qiu, Jun-Ping; Dong, Ke; Yu, Hou-Qiang] Wuhan Univ, Sch Informat Management, Wuhan 430072, Peoples R China.
E-mail Addresses: dongke40 at gmail.com; yuhouq at yeah.net
Funding Acknowledgement: Major Program of the National Social Science Foundation of China [11ZD152]; Humanities and Social Sciences project of Wuhan University [2012GSP032]
Funding Text: This paper is supported by the Major Program of the National Social Science Foundation of China (Grant No. 11&ZD152) and Humanities and Social Sciences project of Wuhan University (Grant No. 2012GSP032).
Cited Reference Count: 62
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900026
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Title: Disciplinary differences in Twitter scholarly communication
Authors: Holmberg, K; Thelwall, M
Author Full Names: Holmberg, Kim; Thelwall, Mike
Source: SCIENTOMETRICS, 101 (2):1027-1042; 10.1007/s11192-014-1229-3<http://dx.doi.org/10.1007/s11192-014-1229-3> NOV 2014
Language: English
Document Type: Article
Author Keywords: Scholarly communication, Twitter, Disciplinary differences, Webometrics, Altmetrics
KeyWords Plus: SOCIAL MEDIA; IMPACT
Abstract: This paper investigates disciplinary differences in how researchers use the microblogging site Twitter. Tweets from selected researchers in ten disciplines (astrophysics, biochemistry, digital humanities, economics, history of science, cheminformatics, cognitive science, drug discovery, social network analysis, and sociology) were collected and analyzed both statistically and qualitatively. The researchers tended to share more links and retweet more than the average Twitter users in earlier research and there were clear disciplinary differences in how they used Twitter. Biochemists retweeted substantially more than researchers in the other disciplines. Researchers in digital humanities and cognitive science used Twitter more for conversations, while researchers in economics shared the most links. Finally, whilst researchers in biochemistry, astrophysics, cheminformatics and digital humanities seemed to use Twitter for scholarly communication, scientific use of Twitter in economics, sociology and history of science appeared to be marginal.
Addresses: [Holmberg, Kim; Thelwall, Mike] Wolverhampton Univ, Dept Math & Comp Sci, Wolverhampton WV1 1LY, W Midlands, England.
E-mail Addresses: k.holmberg at wlv.ac.uk; m.thelwall at wlv.ac.uk
Funding Acknowledgement: Digging into Data international funding initiative through Jisc in the United Kingdom
Funding Text: This research was supported by the Digging into Data international funding initiative through Jisc in the United Kingdom. Parts of the results were presented at the 14th International Society for Scientometrics and Informetrics conference 2013, in Vienna, Austria, and at the ASIS&T European Workshop 2013, in Turku, Finland. Thank you to Andrew Tsou for help with coding the tweets.
Cited Reference Count: 36
Times Cited: 1
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900008
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Title: Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups
Authors: Zhao, RY; Chen, BK
Author Full Names: Zhao, Rongying; Chen, Bikun
Source: SCIENTOMETRICS, 101 (2):985-997; 10.1007/s11192-014-1314-7<http://dx.doi.org/10.1007/s11192-014-1314-7> NOV 2014
Language: English
Document Type: Article
Author Keywords: Webometrics, Usage metrics, Author co-citation analysis, Instant messaging, Social network analysis, Information visualization, Enterprise management
KeyWords Plus: INFORMATION-SCIENCE; INTELLECTUAL STRUCTURE; PATHFINDER NETWORKS; CITATION-INDEX; MAPS; WEB
Abstract: Author co-citation analysis (ACA) was an important method for discovering the intellectual structure of a given scientific field. There was sufficient experience that ACA would work with almost any user data that lent itself to co-occurrence. While most of the current researches still relied on the data of scientific literatures. In this study, in order to provide useful information for better enterprise management, the idea and method of ACA was applied to analyze the information interaction intensity and contents of enterprise web users. Firstly, the development of ACA was briefly introduced. Then the sample data and method used in this study were given. Three QQ groups' instant messages of a Chinese company were selected as the raw data and the concepts and model of user interaction intensity (UII) were proposed by referring the ACA theory. Social network analysis method, combined with in-deep interview method were used to analyze the information interaction intensity and contents of enterprise users. Operatively, Excel, Ucinet, Pajek, Netdraw and VOSviewer software were combined to analyze them quantitatively and visually. Finally, it concluded that UII model was relatively reasonable and it could nicely measure the information interaction intensity and contents of enterprise web users.
Addresses: [Zhao, Rongying; Chen, Bikun] Wuhan Univ, Ctr Studies Informat Resources, Res Ctr China Sci Evaluat, Sch Informat Management, Wuhan 430072, Peoples R China.
E-mail Addresses: chenbikun2011 at whu.edu.cn
Funding Acknowledgement: Major Program of National Social Science Foundation in China [11ZD152]; Social Science Foundation by Ministry of Education in China [13YJA870023]; High-level International Journal Program of Wuhan University [2012GSP062]
Funding Text: This paper is supported by Major Program of National Social Science Foundation in China (Grant No. 11&ZD152), Program of Social Science Foundation by Ministry of Education in China (Grant No. 13YJA870023) and High-level International Journal Program of Wuhan University (Grant No. 2012GSP062). This is an extended version of a paper presented at the 14th International Society of Scientometrics and Informetrics Conference, Vienna (Austria), 15-19 July 2013.
Cited Reference Count: 39
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900005
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Title: Citation impact prediction for scientific papers using stepwise regression analysis
Authors: Yu, T; Yu, G; Li, PY; Wang, L
Author Full Names: Yu, Tian; Yu, Guang; Li, Peng-Yu; Wang, Liang
Source: SCIENTOMETRICS, 101 (2):1233-1252; 10.1007/s11192-014-1279-6<http://dx.doi.org/10.1007/s11192-014-1279-6> NOV 2014
Language: English
Document Type: Article
Author Keywords: Scientific paper, Citation impact prediction, Feature space, Multiple regression
KeyWords Plus: BIOMEDICAL LITERATURE; SCIENCE; COUNTS; JOURNALS; MODELS; INFORMATION; ARTICLES; GENDER
Abstract: Researchers typically pay greater attention to scientific papers published within the last 2 years, and especially papers that may have great citation impact in the future. However, the accuracy of current citation impact prediction methods is still not satisfactory. This paper argues that objective features of scientific papers can make citation impact prediction relatively accurate. The external features of a paper, features of authors, features of the journal of publication, and features of citations are all considered in constructing a paper's feature space. The stepwise multiple regression analysis is used to select appropriate features from the space and to build a regression model for explaining the relationship between citation impact and the chosen features. The validity of this model is also experimentally verified in the subject area of Information Science & Library Science. The results show that the regression model is effective within this subject.
Addresses: [Yu, Tian; Yu, Guang; Wang, Liang] Harbin Inst Technol, Sch Management, Harbin 150006, Peoples R China.
[Li, Peng-Yu] Harbin Inst Technol, Sch Educ, Harbin 150006, Peoples R China.
E-mail Addresses: yutian.hit at gmail.com; yug at hit.edu.cn; lipengyu.hit at gmail.com; hitwangliang at hit.edu.cn
Funding Acknowledgement: National Natural Science Foundation of China [70973031]
Funding Text: This work was supported by the National Natural Science Foundation of China (Grant No. 70973031).
Cited Reference Count: 35
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900020
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Title: Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA
Authors: Lampe, HW; Hilgers, D
Author Full Names: Lampe, Hannes W.; Hilgers, Dennis
Source: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 240 (1):1-21; 10.1016/j.ejor.2014.04.041<http://dx.doi.org/10.1016/j.ejor.2014.04.041> JAN 1 2015
Language: English
Document Type: Review
Author Keywords: Data Envelopment Analysis, Stochastic Frontier Analysis, Literature survey, Citation analysis, Document co-citation analysis
KeyWords Plus: DATA ENVELOPMENT ANALYSIS; STOCHASTIC FRONTIER ANALYSIS; MATHEMATICAL-PROGRAMMING APPROACH; DECISION-MAKING UNITS; SLACKS-BASED MEASURE; MEASURING ENVIRONMENTAL PERFORMANCE; LIFE-INSURANCE INDUSTRY; FOREIGN BANK ENTRY; TECHNICAL EFFICIENCY; NEURAL-NETWORK
Abstract: This study surveys the increasing research field of performance measurement by making use of a bibliometric literature analysis. We concentrate on two approaches, namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) as the most important methods to evaluate the efficiency of individual and organizational performance. It is the first literature survey that analyses DEA and SFA publications jointly, covering contributions published in journals, indexed by the Web of Science database from 1978 to 2012. Our aim is to identify seminal papers, playing a major role in DEA and SFA development and to determine areas of adoption. We recognized a constant growth of publications during the years identifying DEA as a standard technique in Operations Research, whereas SFA is mainly adopted in Economic research fields. Making use of document co-citation analysis we identify Airports and Supplier Selection (DEA) as well as Banking and Agriculture (SFA) as most influential application areas. Furthermore, Sensitivity and Fuzzy Set Theory (DEA) as well as Bayesian Analysis and Heterogeneity (SFA) are found to be most influential research areas and seem to be methodological trends. By developing an adoption rate of knowledge we identify that research, in terms of citations, is more focusing on relatively old and recent research at the expenses of middle-aged contributions, which is a typical phenomenon of a fast developing discipline. (C) 2014 Elsevier B.V. All rights reserved.
Addresses: [Lampe, Hannes W.] Univ Hamburg, D-20146 Hamburg, Germany.
[Hilgers, Dennis] Johannes Kepler Univ Linz, A-4040 Linz, Austria.
E-mail Addresses: Hannes.lampe at wiso.uni-hamburg.de; Dennis.Hilgers at jku.at
Cited Reference Count: 245
Times Cited: 0
Publisher: ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
ISSN: 0377-2217
eISSN: 1872-6860
Web of Science Categories: Management; Operations Research & Management Science
Research Areas: Business & Economics; Operations Research & Management Science
IDS Number: AR1YI
Unique ID: WOS:000343380100001
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Title: 'Seed plus expand': a general methodology for detecting publication oeuvres of individual researchers
Authors: Reijnhoudt, L; Costas, R; Noyons, E; Borner, K; Scharnhorst, A
Author Full Names: Reijnhoudt, Linda; Costas, Rodrigo; Noyons, Ed; Borner, Katy; Scharnhorst, Andrea
Source: SCIENTOMETRICS, 101 (2):1403-1417; 10.1007/s11192-014-1256-0<http://dx.doi.org/10.1007/s11192-014-1256-0> NOV 2014
Language: English
Document Type: Article
Author Keywords: Author disambiguation, Publication oeuvre, Scalable methods
KeyWords Plus: FILTER; OUTPUT; AREA
Abstract: The study of science at the individual scholar level requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e. g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed ? expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980-2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify 'seed publications' for each author using five different approaches. Subsequently, we 'expand' the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a 'gold standard' dataset of authors for which verified publications in the period 2001-2010 are available.
Addresses: [Reijnhoudt, Linda; Borner, Katy; Scharnhorst, Andrea] Royal Netherlands Acad Arts & Sci KNAW, DANS, The Hague, Netherlands.
[Costas, Rodrigo; Noyons, Ed] Leiden Univ, Ctr Sci & Technol Studies CWTS, Leiden, Netherlands.
[Borner, Katy] Indiana Univ, Cyberinfrastruct Network Sci Ctr, Sch Informat & Comp, Bloomington, IN USA.
E-mail Addresses: linda.reijnhoudt at dans.knaw.nl; rcostas at cwts.leidenuniv.nl; noyons at cwts.leidenuniv.nl; katy at indiana.edu; andrea.scharnhorst at dans.knaw.nl
Funding Acknowledgement: NoE European InterNet Science (EINS) (EC) [288021]; National Institutes of Health [U01 GM098959]
Funding Text: The authors acknowledge detailed comments and suggestions provided by Vincent Lariviere and Kevin W. Boyak on an early version of this manuscript. Part of this work was funded by the NoE European InterNet Science (EINS) (EC Grant 288021) and the National Institutes of Health under award U01 GM098959.
Cited Reference Count: 25
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900030
Cited References:
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Title: Assessing obliteration by incorporation in a full-text database: JSTOR, Economics, and the concept of "bounded rationality"
Authors: McCain, K
Author Full Names: McCain, Katherine W.
Source: SCIENTOMETRICS, 101 (2):1445-1459; 10.1007/s11192-014-1237-3<http://dx.doi.org/10.1007/s11192-014-1237-3> NOV 2014
Language: English
Document Type: Article
Author Keywords: Obliteration by incorporation, Economics, Full-text databases, Citation-in-context analysis
KeyWords Plus: CUMULATIVE ADVANTAGE; CITATION ANALYSIS; SCIENCE; PUBLICATION; DOCUMENTS; JOURNALS; EPONYMY
Abstract: To evaluate the usefulness of a full-text database as a source for assessing obliteration by incorporation (OBI), 3,707 article records including the catchphrases "bounded rationality" and/or "boundedly rational" (connected with the work of H. A. Simon) in the article text were retrieved from JSTOR, a full-text database with broad disciplinary coverage. Two subsets were analyzed-a 10 % systematic sample of all records and a set of all articles in Economics journals (with the addition of the Journal of Economic Theory). A majority of articles in the 10 % sample came from Economics and Management journals, while Psychology was poorly represented. In the 10 % sample, based on the percentage of true implicit citations between 1992 and 2009 in the 80 % of records that had a catchphrase in the body of the article, rather than just in the reference list, annual OBI ranged from 0 to 70 % (mean 33 %) with no discernible trend. The Economics articles showed a narrower range of OBI-fluctuating around 40 % implicit citations over the same time period. In both data sets, a large proportion of indirect citations were to sources that themselves cited a relevant work by Simon. Over 90 % of the articles in both the 10 % sample and the economics journal set would not have been retrieved with a database record search because they lacked the catchphrase in the record fields.
Addresses: Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.
E-mail Addresses: mccainkw at drexel.edu
Cited Reference Count: 28
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900033
Cited References:
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Title: Which role do non-source items play in the social sciences? A case study in political science in Germany
Authors: Chi, PS
Author Full Names: Chi, Pei-Shan
Source: SCIENTOMETRICS, 101 (2):1195-1213; 10.1007/s11192-014-1433-1<http://dx.doi.org/10.1007/s11192-014-1433-1> NOV 2014
Language: English
Document Type: Article
Author Keywords: Non-source items, Social sciences, Publication patterns, Research evaluation, Political science
KeyWords Plus: RESEARCH PERFORMANCE; PUBLICATION PATTERNS; BEHAVIORAL-SCIENCES; CITATION ANALYSIS; HUMANITIES; INDICATORS; COVERAGE; BIBLIOMETRICS; SOCIOLOGY; OUTPUT
Abstract: Publications that are not indexed by citation indices such as Web of Science (WoS) or Scopus are called "non-source items". These have so far been neglected by most bibliometric analyses. The central issue of this study is to investigate the characteristics of non-source items and the effect of their inclusion in bibliometric evaluations in the social sciences, specifically German political science publications. The results of this study show that non-source items significantly increase the number of publications (+1,350 %) and to a lesser extent the number of citations from SCIE, SSCI, and A&HCI (+150 %) for evaluated political scientists. 42 % of non-source items are published as book chapters. Edited books and books are cited the most among non-source items. About 40 % of non-source items are in English, while 80 % of source items are in English. The citation rates of researchers taking non-source items into account are lower than those from source items, partially as a result of the limited coverage of WoS. In contrast, the H-indices of researchers taking only non-source items into account are higher than those from source items. In short, the results of this study show that non-source items should be included in bibliometric evaluations, regardless of their impact or the citations from them. The demand for a more comprehensive coverage of bibliometric database in the social sciences for a higher quality of evaluations is shown.
Addresses: Inst Res Informat & Qual Assurance, D-10117 Berlin, Germany.
E-mail Addresses: peishan.chi at kuleuven.be
Funding Acknowledgement: German Federal Ministry for Education and Research (BMBF) [01PQ08004A]
Funding Text: This study is based on a previous work presented at 14th ISSI 2013 in Vienna (Chi 2013), and supported by the German Federal Ministry for Education and Research (BMBF, project number 01PQ08004A). The author would like to thank William Dinkel, Paul Donner, Sybille Hinze, Stefan Hornbostel, Vivien Petras, Jasmin Schmitz, Daniel Sirtes, Andreas Strotmann, Jian Wang, and Manuela Zinnbauer, those who contribute to improve the current and previous versions, and two reviewers for providing valuable comments on this paper. The citation data used in this paper are from a bibliometric database developed and maintained by the Competence Center for Bibliometrics for the German Science System (KB) and derived from the 2003 to 2012 Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts and Humanities Citation Index (A&HCI) provided by Thomson Reuters (Scientific) Inc. (TR (R)), Philadelphia, Pennsylvania, USA: (c) Copyright Thomson Reuters (Scie! ntific) 2012.
Cited Reference Count: 41
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900018
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Title: An insight into the importance of national university rankings in an international context: the case of the I-UGR rankings of Spanish universities
Authors: Robinson-Garcia, N; Torres-Salinas, D; Lopez-Cozar, ED; Herrera, F
Author Full Names: Robinson-Garcia, Nicolas; Torres-Salinas, Daniel; Delgado Lopez-Cozar, Emilio; Herrera, Francisco
Source: SCIENTOMETRICS, 101 (2):1309-1324; 10.1007/s11192-014-1263-1<http://dx.doi.org/10.1007/s11192-014-1263-1> NOV 2014
Language: English
Document Type: Article
Author Keywords: Universities, Spain, International rankings, National rankings, Research evaluation
KeyWords Plus: RESEARCH PERFORMANCE; INSTITUTIONS; INDEX
Abstract: The great importance international rankings have achieved in the research policy arena warns against many threats consequence of the flaws and shortcomings these tools present. One of them has to do with the inability to accurately represent national university systems as their original purpose is only to rank world-class universities. Another one has to do with the lack of representativeness of universities' disciplinary profiles as they usually provide a unique table. Although some rankings offer a great coverage and others offer league tables by fields, no international ranking does both. In order to surpass such limitation from a research policy viewpoint, this paper analyzes the possibility of using national rankings in order to complement international rankings. For this, we analyze the Spanish university system as a study case presenting the I-UGR Rankings for Spanish universities by fields and subfields. Then, we compare their results with those obtained by the Shanghai Ranking, the QS Ranking, the Leiden Ranking and the NTU Ranking, as they all have basic common grounds which allow such comparison. We conclude that it is advisable to use national rankings in order to complement international rankings, however we observe that this must be done with certain caution as they differ on the methodology employed as well as on the construction of the fields.
Addresses: [Robinson-Garcia, Nicolas; Delgado Lopez-Cozar, Emilio] Univ Granada, Dept Bibliotecon & Documentac, EC3, Granada, Spain.
[Torres-Salinas, Daniel] Univ Navarra, Ctr Invest Biomed Aplicada, EC3, Navarra, Spain.
[Herrera, Francisco] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain.
E-mail Addresses: elrobin at ugr.es; torressalinas at gmail.com; edelgado at ugr.es; herrera at decsai.ugr.es
Funding Acknowledgement: FPU Grant from the Ministerio de Educacion y Ciencia of the Spanish Government
Funding Text: Thanks are due to the two anonymous referees for their helpful comments. Nicolas Robinson-Garcia is currently supported by a FPU Grant from the Ministerio de Educacion y Ciencia of the Spanish Government.
Cited Reference Count: 26
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900024
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Title: Literature retrieval based on citation context
Authors: Liu, SB; Chen, CM; Ding, K; Wang, B; Xu, K; Lin, Y
Author Full Names: Liu, Shengbo; Chen, Chaomei; Ding, Kun; Wang, Bo; Xu, Kan; Lin, Yuan
Source: SCIENTOMETRICS, 101 (2):1293-1307; 10.1007/s11192-014-1233-7<http://dx.doi.org/10.1007/s11192-014-1233-7> NOV 2014
Language: English
Document Type: Article
Author Keywords: Literature retrieval, Citation context, Tag cloud, Citation context classification
KeyWords Plus: COMPUTER RECOGNITION; CITING STATEMENTS; COCITATION
Abstract: While the citation context of a reference may provide detailed and direct information about the nature of a citation, few studies have specifically addressed the role of this information in retrieving relevant documents from the literature primarily due to the lack of full text databases. In this paper, we design a retrieval system based on full texts in the PubMed Central database. We constructed two modules in the retrieval system. One is a reference retrieval module based on citation contexts. Another is a citation context retrieval module for searching the citation contexts of a specific paper. The results of comparisons show that the reference retrieval module performed better than Google Scholar and PubMed database in terms of finding proper references based on topic words extracted from citation context. It also performed very well on searching highly cited papers and classic papers. The citation context retrieval module visualizes the topics of citation contexts as tag clouds and classifies citation contexts based on cue words in citation contexts.
Addresses: [Liu, Shengbo; Ding, Kun; Wang, Bo] Dalian Univ Technol, WISElab, Dalian 116024, Peoples R China.
[Chen, Chaomei] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.
[Ding, Kun; Lin, Yuan] Dalian Univ Technol, Informat Retrieval Lab, Dalian 116024, Peoples R China.
E-mail Addresses: liushengbo1121 at gmail.com; chaomei.chen at drexel.edu; dingk at dlut.edu.cn; bowang1121 at gmail.com; xukan at dlut.edu.cn; zhlin at dlut.edu.cn
Funding Acknowledgement: National Natural Science Foundation of China [61272370]; specialized research fund for doctoral tutor [20110041110034]; Fundamental Research Funds for the Central Universities; iSchool at Drexel University
Funding Text: This research is supported by National Natural Science Foundation of China (grant number 61272370), the specialized research fund for doctoral tutor (20110041110034), and the Fundamental Research Funds for the Central Universities. Part of the research was conducted during Shengbo Liu's visiting doctoral studentship at the iSchool at Drexel University.
Cited Reference Count: 31
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900023
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Title: Comparative study on structure and correlation among author co-occurrence networks in bibliometrics
Authors: Qiu, JP; Dong, K; Yu, HQ
Author Full Names: Qiu, Jun-Ping; Dong, Ke; Yu, Hou-Qiang
Source: SCIENTOMETRICS, 101 (2):1345-1360; 10.1007/s11192-014-1315-6<http://dx.doi.org/10.1007/s11192-014-1315-6> NOV 2014
Language: English
Document Type: Article
Author Keywords: Co-authorship analysis, Author co-citation analysis, Author bibliographic coupling, Correlation analysis, Bibliometrics
KeyWords Plus: PEARSONS CORRELATION-COEFFICIENT; BIBLIOGRAPHIC-COUPLING ANALYSIS; INFORMATION-SCIENCE; COCITATION ANALYSIS; CO-AUTHORSHIP; SCIENTIFIC COLLABORATION; COAUTHORSHIP NETWORKS; INTELLECTUAL SPACE; ALL-AUTHOR; CITATION
Abstract: This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.
Addresses: [Qiu, Jun-Ping; Dong, Ke; Yu, Hou-Qiang] Wuhan Univ, Sch Informat Management, Wuhan 430072, Peoples R China.
E-mail Addresses: dongke40 at gmail.com; yuhouq at yeah.net
Funding Acknowledgement: Major Program of the National Social Science Foundation of China [11ZD152]; Humanities and Social Sciences project of Wuhan University [2012GSP032]
Funding Text: This paper is supported by the Major Program of the National Social Science Foundation of China (Grant No. 11&ZD152) and Humanities and Social Sciences project of Wuhan University (Grant No. 2012GSP032).
Cited Reference Count: 62
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900026
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Title: Relationship between downloads and citations at journal and paper levels, and the influence of language
Authors: Guerrero-Bote, VP; Moya-Anegon, F
Author Full Names: Guerrero-Bote, Vicente P.; Moya-Anegon, Felix
Source: SCIENTOMETRICS, 101 (2):1043-1065; 10.1007/s11192-014-1243-5<http://dx.doi.org/10.1007/s11192-014-1243-5> NOV 2014
Language: English
Document Type: Article
Author Keywords: Scientometric indicators, Download indicator, Citation indicators, Language influence, Scopus, ScienceDirect
KeyWords Plus: ICEBERG HYPOTHESIS; IMPACT; BOOKS; DISCIPLINES; SCHOLARSHIP; INDICATORS; HUMANITIES; SOCIOLOGY; RANKINGS; CAREERS
Abstract: Download indicators are of major potential interest because the great quantity of readily available download data means that any statistical inferences drawn from them will be of robust significance. We study the relationship between citation and downloads at the journal and paper levels, and the influence of language on that relationship. The data used were taken from the Scopus (citations) and ScienceDirect (downloads) databases. The results showed that downloads have limited utility as predictors of citation since it is in the early years when any correlations have the least significance. The relationship between downloads and citation also differs from one discipline to another. The relationship at the paper level is considerably weaker than at the journal level. This may be indicative of the number of downloads depending largely on the diffusion of the journal. In francophone regions, downloading from journals is proportionately less than citations to those same journals. There seems to be a part of citations to non-English-language journals which is invisible to Scopus. This makes the number of downloads proportionately greater than that of citations, leading to a lack of correlation between downloads and citations in that class of journal.
Addresses: [Guerrero-Bote, Vicente P.] Univ Extremadura, Dept Informac & Comunicac, Grp Scimago, E-06071 Badajoz, Spain.
[Moya-Anegon, Felix] CSIC, IPP, CCHS, Grp Scimago, Madrid 28037, Spain.
E-mail Addresses: guerrero at unex.es; felix.demoya at cchs.csic.es
Funding Acknowledgement: Elsevier as part of the Elsevier Bibliometric Research Program (EBRP); Junta de Extremadura, Consejeria de Empleo, Empresa e Innovacion; Fondo Social Europeo as part of the research group Grant [GR10019]
Funding Text: This work was supported by Elsevier as part of the Elsevier Bibliometric Research Program (EBRP), and financed by the Junta de Extremadura, Consejeria de Empleo, Empresa e Innovacion and by the Fondo Social Europeo as part of the research group Grant GR10019.
Cited Reference Count: 37
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900009
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Title: The citer-success-index: a citer-based indicator to select a subset of elite papers
Authors: Franceschini, F; Maisano, D; Mastrogiacomo, L
Author Full Names: Franceschini, Fiorenzo; Maisano, Domenico; Mastrogiacomo, Luca
Source: SCIENTOMETRICS, 101 (2):963-983; 10.1007/s11192-014-1250-6<http://dx.doi.org/10.1007/s11192-014-1250-6> NOV 2014
Language: English
Document Type: Article
Author Keywords: Impact, Citations, References, Citation propensity, Success-index, Citers, Cited authors
KeyWords Plus: IMPACT; PUBLICATIONS
Abstract: The goal of this paper is introducing the citer-success-index (cs-index), i.e. an indicator that uses the number of different citers as a proxy for the impact of a generic set of papers. For each of the articles of interest, it is defined a comparison term-which represents the number of citers that, on average, an article published in a certain period and scientific field is expected to "infect"-to be compared with the actual number of citers of the article. Similarly to the recently proposed success-index (Franceschini et al. Scientometrics 92(3): 621-6415, 2011), the cs-index allows to select a subset of "elite" papers. The cs-index is analyzed from a conceptual and empirical perspective. Special attention is devoted to the study of the link between the number of citers and cited authors relating to articles from different fields, and the possible correlation between the cs- and the success-index. Some advantages of the cs-index are that (i) it can be applied to multidisciplinary groups of papers, thanks to the field-normalization that it achieves at the level of individual paper and (ii) it is not significantly affected by self citers and recurrent citers. The main drawback is its computational complexity.
Addresses: [Franceschini, Fiorenzo; Maisano, Domenico; Mastrogiacomo, Luca] DIGEP, Politecn Torino, Dept Management & Prod Engn, I-10129 Turin, Italy.
E-mail Addresses: fiorenzo.franceschini at polito.it; domenico.maisano at polito.it; luca.mastrogiacomo at polito.it
Cited Reference Count: 24
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900004
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Title: How do you define and measure research productivity?
Authors: Abramo, G; D'Angelo, CA
Author Full Names: Abramo, Giovanni; D'Angelo, Ciriaco Andrea
Source: SCIENTOMETRICS, 101 (2):1129-1144; 10.1007/s11192-014-1269-8<http://dx.doi.org/10.1007/s11192-014-1269-8> NOV 2014
Language: English
Document Type: Article
Author Keywords: Research productivity, FSS, Research evaluation, University rankings
KeyWords Plus: RESEARCH PERFORMANCE; LIFE SCIENCES; CITATIONS; NATIONS; AUTHORS; IMPACT; ORDER; TIME
Abstract: Productivity is the quintessential indicator of efficiency in any production system. It seems it has become a norm in bibliometrics to define research productivity as the number of publications per researcher, distinguishing it from impact. In this work we operationalize the economic concept of productivity for the specific context of research activity and show the limits of the commonly accepted definition. We propose then a measurable form of research productivity through the indicator "Fractional Scientific Strength (FSS)", in keeping with the microeconomic theory of production. We present the methodology for measure of FSS at various levels of analysis: individual, field, discipline, department, institution, region and nation. Finally, we compare the ranking lists of Italian universities by the two definitions of research productivity.
Addresses: [Abramo, Giovanni; D'Angelo, Ciriaco Andrea] Natl Res Council Italy, CNR, Inst Syst Anal & Comp Sci IASI, Lab Studies Res & Technol Transfer, I-00185 Rome, Italy.
[D'Angelo, Ciriaco Andrea] Univ Roma Tor Vergata, Dept Engn & Management, I-00133 Rome, Italy.
E-mail Addresses: giovanni.abramo at uniroma2.it; dangelo at dii.uniroma2.it
Cited Reference Count: 38
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900014
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Title: Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups
Authors: Zhao, RY; Chen, BK
Author Full Names: Zhao, Rongying; Chen, Bikun
Source: SCIENTOMETRICS, 101 (2):985-997; 10.1007/s11192-014-1314-7<http://dx.doi.org/10.1007/s11192-014-1314-7> NOV 2014
Language: English
Document Type: Article
Author Keywords: Webometrics, Usage metrics, Author co-citation analysis, Instant messaging, Social network analysis, Information visualization, Enterprise management
KeyWords Plus: INFORMATION-SCIENCE; INTELLECTUAL STRUCTURE; PATHFINDER NETWORKS; CITATION-INDEX; MAPS; WEB
Abstract: Author co-citation analysis (ACA) was an important method for discovering the intellectual structure of a given scientific field. There was sufficient experience that ACA would work with almost any user data that lent itself to co-occurrence. While most of the current researches still relied on the data of scientific literatures. In this study, in order to provide useful information for better enterprise management, the idea and method of ACA was applied to analyze the information interaction intensity and contents of enterprise web users. Firstly, the development of ACA was briefly introduced. Then the sample data and method used in this study were given. Three QQ groups' instant messages of a Chinese company were selected as the raw data and the concepts and model of user interaction intensity (UII) were proposed by referring the ACA theory. Social network analysis method, combined with in-deep interview method were used to analyze the information interaction intensity and contents of enterprise users. Operatively, Excel, Ucinet, Pajek, Netdraw and VOSviewer software were combined to analyze them quantitatively and visually. Finally, it concluded that UII model was relatively reasonable and it could nicely measure the information interaction intensity and contents of enterprise web users.
Addresses: [Zhao, Rongying; Chen, Bikun] Wuhan Univ, Ctr Studies Informat Resources, Res Ctr China Sci Evaluat, Sch Informat Management, Wuhan 430072, Peoples R China.
E-mail Addresses: chenbikun2011 at whu.edu.cn
Funding Acknowledgement: Major Program of National Social Science Foundation in China [11ZD152]; Social Science Foundation by Ministry of Education in China [13YJA870023]; High-level International Journal Program of Wuhan University [2012GSP062]
Funding Text: This paper is supported by Major Program of National Social Science Foundation in China (Grant No. 11&ZD152), Program of Social Science Foundation by Ministry of Education in China (Grant No. 13YJA870023) and High-level International Journal Program of Wuhan University (Grant No. 2012GSP062). This is an extended version of a paper presented at the 14th International Society of Scientometrics and Informetrics Conference, Vienna (Austria), 15-19 July 2013.
Cited Reference Count: 39
Times Cited: 0
Publisher: SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 0138-9130
eISSN: 1588-2861
Web of Science Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
Research Areas: Computer Science; Information Science & Library Science
IDS Number: AR5FF
Unique ID: WOS:000343609900005
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Title: Bibliometrics: Is your most cited work your best?
Authors: Ioannidis, JPA; Boyack, KW; Small, H; Sorensen, AA; Klavans, R
Author Full Names: Ioannidis, John P. A.; Boyack, Kevin W.; Small, Henry; Sorensen, Aaron A.; Klavans, Richard
Source: NATURE, 514 (7524):561-562; OCT 30 2014
Language: English
Document Type: Editorial Material
Addresses: [Ioannidis, John P. A.] Stanford Univ, Meta Res Innovat Ctr Stanford METRICS, Stanford, CA 94305 USA.
[Boyack, Kevin W.] SciTech Strategies, Albuquerque, NM USA.
[Small, Henry] SciTech Strategies, Bala Cynwyd, PA USA.
[Sorensen, Aaron A.] Temple Univ, Sch Med, Philadelphia, PA 19122 USA.
[Klavans, Richard] SciTech Strategies, Berwyn, PA USA.
Cited Reference Count: 8
Times Cited: 0
Publisher: NATURE PUBLISHING GROUP, MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
ISSN: 0028-0836
eISSN: 1476-4687
Web of Science Categories: Multidisciplinary Sciences
Research Areas: Science & Technology - Other Topics
IDS Number: AR8BW
Unique ID: WOS:000343801500024
PubMed ID: 25355346
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