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Treffer: Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups

Title:
Applying author co-citation analysis to user interaction analysis: a case study on instant messaging groups
Authors:
RONGYING ZHAO, BIKUN CHEN
Source:
Selected Papers of the 14th International Conference of the International Society for Scientometrics and Informetrics (ISSI), July 15-19, 2013, Vienna, AustriaScientometrics (Print). 101(2):985-997
Publisher Information:
Dordrecht: Springer, 2014.
Publication Year:
2014
Physical Description:
print, 1 p.1/4
Original Material:
INIST-CNRS
Subject Terms:
Information and communication sciences, Sciences de l'information communication, Documentation, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Sciences de l'information. Documentation, Information science. Documentation, Sciences de l'information et des bibliothèques. Etude d'ensemble, Library and information science. General aspects, Bibliométrie. Scientométrie. Evaluation, Bibliometrics. Scientometrics. Evaluation, Sciences de l'information et de la communication, Information and communication sciences, Bibliométrie. Scientométrie, Bibliometrics. Scientometrics, Analyse coauteur, Coauthorship analysis, Análisis coautor, Analyse cocitation, Cocitation analysis, Análisis cocitacion, Domaine recherche, Research field, Campo investigación, Infométrie, Informetrics, Infometría, Littérature scientifique, Scientific literature, Literatura científica, Méthode analyse, Analysis method, Método análisis, Métrique, Metric, Métrico, Recherche scientifique, Scientific research, Investigación científica, Webométrie, Webometrics, Webometría, 91C20, Author co-citation analysis, C92, Enterprise management, Information visualization, Instant messaging, Social network analysis, Usage metrics
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Information Management, Research Center for China Science Evaluation, The Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
ISSN:
0138-9130
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28892087
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation

FRANCIS
Accession Number:
edscal.28892087
Database:
PASCAL Archive

Weitere Informationen

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.