hrd685 presentation interesting version

CO-AUTHOR COLLABORATION NETWORK FIGURE IN THE 2010 AHRD

CONFERENCE SYMPOSIUM PAPERSA MASTER DEGREE PROJECT PRESENTED TO

PROFESSIONAL STUDIES COLLEGE OF TECHNOLOGY

INDIANA STATE UNIVERSITY, TERRE HAUTE, INDIANA

CHUNGIL CHAE (CHAD)

Saturday, December 8, 12

TABLE OF CONTENTS

INTRODUCTION

LITERATURE REVIEW

METHODOLOGY

RESULT

CONCLUSIONLITERATURE REVIEW

INTRODUCTION

THERE IS A DIFFICULTY

PURPOSE AND NEED

OBJECTIVES

WHAT IS COLLABORATION NETWORK?

WHIT IS INTERESTING?

WHAT IS SOCIAL NETWORK ANALYSIS?

THERE IS A DIFFICULTY

IDENTIFYING CO-AUTHOR COLLABORATION NETWORKINGS.

IT IS ASSUMED BY THE CONFERENCE PROCEEDING

ASSUMPTIONS CANNOT PROVIDE A PLENTIFUL EXPLANATION OF THE CO-AUTHOR COLLABORATION NETWORK.

PURPOSE AND NEED

USING SOCIAL NETWORK ANALYSIS (SNA) ON THE 2010 AHRD PROCEEDING PAPERS PROVIDES A CLEAR VIEW OF HOW THEY ARE CONNECTED AND PROVIDES AN ACKNOWLEDGEMENT OF AHRD COLLABORATION NETWORKING FEATURES.

OBJECTIVES

1. IDENTIFYING 2010 AHRD CONFERENCE’S CO-AUTHOR COLLABORATION NETWORK

2. DETECTING THE EXISTENCE OF THE NOTICEABLE CLUSTERS OF THE NETWORK.

3. INVESTIGATING THE DETECTED NOTICEABLE CLUSTER’S CHARACTERISTICS.

TERMSACTOR THE LINKAGES AMONG SOCIAL ENTITIES AND THE IMPLICATIONS OF THESE LINKAGES. THE SOCIAL ENTITIES ARE REFERRED TO AS ACTORS

RELATIONAL TIE RELATIONAL TIE INDICATES A TIE ESTABLISHING A LINKAGE BETWEEN A PAIR OF ACTORS (WASSERMAN & FAUST, 1994)

GROUPSA GROUP IS THE COLLECTION OF ALL ACTORS ON WHICH TIES ARE TO BE MEASURED (SCOTT, 2000; WASSERMAN & FAUST, 1994).

LITERATURE REVIEW

COLLABORATION NETWORK

THE 2010 AHRD INTERNATIONAL CONFERENCE

SOCIAL NETWORK ANALYSIS

NETMINER

COLLABORATION NETWORK

A COLLABORATION NETWORK IS :

A NETWORK THAT IS CONSTITUTED OF PEOPLE AS ACTORS AND COLLABORATION RESULTS AS RELATIONAL TIES. A COLLABORATION NETWORK IS REGARDED AS AN INTENTIONAL PROPERTY THAT DERIVES FROM THE SHARED BELIEF THAT IS SET BY THE COLLABORATION PARTICIPANT’S COMMON GOAL OF AVOIDING THE FAILURE TO SUCCEED OR INCURRING TOO HIGH OF A COST IF THEY ARE CONDUCTING THE PROJECT INDIVIDUALLY (CAMARINHA-MATOS & AFSARMANESH, 2005)

THE 2010 AHRD INTERNATIONAL CONFERENCE

THE ACADEMY OF HUMAN RESOURCE DEVELOPMENT (AHRD) IS A PROFESSIONAL AND SCHOLASTIC COMMUNITY. SINCE 1994, AHRD BEGAN HAVING INTERNATIONAL CONFERENCES

THE 2010 AHRD INTERNATIONAL CONFERENCE IS THE 17TH INTERNATIONAL CONFERENCE IN THE AHRD COMMUNITY.

THE 2010 AHRD INTERNATIONAL CONFERENCE RESEARCH PAPERS HAVE A SIGNIFICANT MEANING IN THIS PROJECT BECAUSE OF THE AHRD COMMUNITY’S ATTRIBUTION AS THE AFFILIATION NETWORK

SOCIAL NETWORK ANALYSIS (SNA) IS A FIELD THAT VIEWS SOCIAL PHENOMENON AS RESULTS AND COMBINATIONS OF SOCIALLY CONNECTED RELATIONSHIPS, WHICH INTERACTIVELY INFLUENCE EACH OTHER (WASSERMAN & FAUST, 1994)

NETMINER

NETMINER III (VERSION 3.4.0D; CYRAM 2010) IS A SOFTWARE TOOL FOR EXPLORATORY ANALYSIS AND VISUALIZATION OF NETWORK DATA (NETMINER, 2010B).

LICENSE TERM DATA SIZE

STUDENT

ACADEMY

COMMERCIAL

3˜6 MONTH 100˜1,000

ANNUAL/PERPETUAL 1,000˜1,000,000

PERPETUAL 1,000˜1,000,000

METHODOLOGYSUBJECT

DATA COLLECTION

DATA PROCESS PROCEDURE

SUBJECT

AS A RESULT, 115 SYMPOSIUM PAPERS, 184 AUTHORS AND 93 INSTITUTIONS ARE SELECTED

DATA COLLECTION

DATA ARE COLLECTED FROM THE 2010 AHRD INTERNATIONAL CONFERENCE PROCEEDING. PROCEEDING INCLUDES SYMPOSIUM NUMBERS, AUTHORS AND INSTITUTIONS. THIS PROJECT’S INVESTIGATOR ABSTRACTS ALL DATA FROM PROCEEDINGS. COLLECTED DATA ARE REORGANIZED IN THE FORM OF SOCIAL NETWORK DATA SUCH AS MODE-1 AND MODE-2

Objectives1: Identifying 2010 AHRD conferenceʼs co-author collaboration network

Activity1: raw data collecting

Task1: Data abstracting

1 STEP: Abstract author, papers, university data from proceeding

2 STEP: Making excel files paper-author, paper-university, Uniersity-author

Task2: Data sorting and purifying

1 STEP: Delet redundunce entry

2 STEP: sorting by a-z

Activity2: Data upload

Task1: Data type deciding

1 STEP: 1-mode data

2 STEP: 2-mode data

Task2: Data upload

1 STEP: 1-mode data

2 STEP: 2-mode data

Task3: Data check

1 STEP: comparing uploaded data and actual data

Activity3: Data processing

Task1: Data drawing

Step1: Spring 2D P-A, P-U,U-A

Objectives3: Investigating noticeable clusterʼs characteristics

Activity1: Connection

Task 1: Running Analysis

1 STEP: Degree mean

2 STEP: Density

3 STEP: inclusiveness

4 STEP: Geodesic distance

5 STEP: Redundancy

Activity2: Centerality

1 STEP: degree centtrality-symmetrized

2 STEP: eigenvector centrality

3 STEP: closeness centality

4 STEP: betweenness centrality

Activity3: Cohesion

1 STEP: component

2 STEP: clique

3 STEP: structural equivalence

Objectives2: Detecting existence of the noticeable cluster of the networking

Drawing edged structureTask 1: 1

mode data

1 STEP: Edge clustering / Paper-Author

2 STEP: Edge clustering / Paper-University

3 STEP: Edge clustering / Univerisity-Author

Task 2: 2 mode data

1 STEP:Edge clustering / Paper-Author

2 STEP:Edge clustering / Paper-University

3 STEP:Edge clustering / Univerisity-Author

RESULTOBJECTIVE 1OBJECTIVE IIOBJECTIVE III

OBJECTIVE I1. IDENTIFYING 2010 AHRD

CONFERENCE’S CO-AUTHOR COLLABORATION NETWORK

OBJECTIVE I1. IDENTIFYING 2010 AHRD

CONFERENCE’S CO-AUTHOR COLLABORATION NETWORK

OBJECTIVE II2. DETECTING THE EXISTENCE OF

THE NOTICEABLE CLUSTERS OF THE NETWORK.

OBJECTIVE III3. INVESTIGATING THE DETECTED

NOTICEABLE CLUSTER’S CHARACTERISTICS.

OBJECTIVE III3. INVESTIGATING THE DETECTED

NOTICEABLE CLUSTER’S CHARACTERISTICS.

CONCLUSIONCONCLUSION

IMPLICATIONS

CONCLUSIONTHE 2010 AHRD CONFERENCE’S CO-AUTHOR COLLABORATION NETWORK STRUCTURE HAS BEEN MAPPED

IDENTIFIED WHOLE FEATURES OF THE NETWORK ARE REORGANIZED BY CENTERING ITS EDGES. THEREBY, NOTICEABLE SUBGROUPS’ EXISTENCE AND ITS STRUCTURAL NETWORKING WERE IDENTIFIED.

THE NETWORK’S CHARACTERISTICS HAVE BEEN PRESENTED BY CONDUCTING A SERIES OF ANALYSES IN ASPECTS OF CONNECTIVITY, CENTRALITY, AND COHESION.

THE WHOLE NETWORK’S STRUCTURE AND SIZE ARE SUGGESTED.

THE 2010 AHRD CONFERENCE’S COAUTHORSHIP COLLABORATION DIDN’T HAVE A HIGH DENSITY OF CONNECTIVITY, BUT THE CENTRALITY WAS EMPHASIZED ON A FEW NODES

REFERENCE LIST

AHUJA, G. (2000). COLLABORATION NETWORKS, STRUCTURAL HOLES, AND INNOVATION: A LONGITUDINAL STUDY. ADMINISTRATIVE SCIENCE QUARTERLY, 425-455.

CAMARINHA-MATOS, L., & AFSARMANESH, H. (2005). COLLABORATIVE NETWORKS: A NEW SCIENTIFIC DISCIPLINE. JOURNAL OF INTELLIGENT MANUFACTURING, 16(4), 439-452.

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EVANS, P., & WOLF, B. (2005). COLLABORATION RULES. IEEE ENGINEERING MANAGEMENT REVIEW, 33(4), 50-57.

REFERENCE LIST

FREEMAN, L. (2004). THE DEVELOPMENT OF SOCIAL NETWORK ANALYSIS: EMPIRICAL PRESS VANCOUVER, BRITISH COLUMBIA.

GRAHAM, C. M. (2010). 2010 CONFERENCE PROCEEDINGS. PAPER PRESENTED AT THE 2010 AHRD INTERNATIONAL RESEARCH CONFERENCE, KNOXVILLE, TENNESSEE, USA.

HEIMERIKS, G., HOERLESBERGER, M., & VAN DEN BESSELAAR, P. (2003). MAPPING COMMUNICATION AND COLLABORATION IN HETEROGENEOUS RESEARCH NETWORKS. SCIENTOMETRICS, 58(2), 391-413.

HUYSMAN, M., & WULF, V. (2006). IT TO SUPPORT KNOWLEDGE SHARING IN COMMUNITIES, TOWARDS A SOCIAL CAPITAL ANALYSIS. JOURNAL OF INFORMATION TECHNOLOGY, 21(1), 40-51.

MA, Z., & YU, K.-H. (2010). RESEARCH PARADIGMS OF CONTEMPORARY KNOWLEDGE MANAGEMENT STUDIES: 1998-2007. JOURNAL OF KNOWLEDGE MANAGEMENT, 14(2).

REFERENCE LIST

MITCHELL, J. (1969). SOCIAL NETWORKS IN URBAN SITUATIONS: ANALYSES OF PERSONAL RELATIONSHIPS IN CENTRAL AFRICAN TOWNS: HUMANITIES PRESS INTL.

MOODY, J. (2004). THE STRUCTURE OF A SOCIAL SCIENCE COLLABORATION NETWORK: DISCIPLINARY COHESION FROM 1963 TO 1999. AMERICAN SOCIOLOGICAL REVIEW, 69(2), 213.

NETMINER. (2010A). LICENSE. RETRIEVED OCT 15, 2010, FROM HTTP://WWW.NETMINER.COM/NETMINER/PRODUCT_04.JSP

NETMINER. (2010B). NETMINER OVERVIEW. RETRIEVED OCT 20, 2010, FROM HTTP://WWW.NETMINER.COM/NETMINER/OVERVIEW_01.JSP

NEWMAN, M. (2001A). SCIENTIFIC COLLABORATION NETWORKS. I. NETWORK CONSTRUCTION AND FUNDAMENTAL RESULTS. PHYSICAL REVIEW E, 64(1), 16131.

REFERENCE LIST

NEWMAN, M. (2001B). SCIENTIFIC COLLABORATION NETWORKS. II. SHORTEST PATHS, WEIGHTED NETWORKS, AND CENTRALITY. PHYSICAL REVIEW E, 64(1), 16132.

NEWMAN, M. (2004). COAUTHORSHIP NETWORKS AND PATTERNS OF SCIENTIFIC COLLABORATION. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES, 101(SUPPL 1), 5200.

PUTSCH, F. (2003). ANALYSIS AND MODELING OF SCIENCE COLLABORATION NETWORKS. ARXIV PREPRINT COND-MAT/0305112.

RAMASCO, J., DOROGOVTSEV, S., & PASTOR-SATORRAS, R. (2004). SELF-ORGANIZATION OF COLLABORATION NETWORKS. PHYSICAL REVIEW E, 70(3), 36106.

REFFAY, C., & CHANIER, T. (2002). SOCIAL NETWORK ANALYSIS USED FOR MODELLING COLLABORATION IN DISTANCE LEARNING GROUPS.

REFERENCE LIST

SENGE, P. (1993). THE FIFTH DISCIPLINE. MEASURING BUSINESS EXCELLENCE, 1(3), 46-51.

SMITH, R. (2006). THE NETWORK OF COLLABORATION AMONG RAPPERS AND ITS COMMUNITY STRUCTURE. JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT, 2006, P02006.

TICHY, N., TUSHMAN, M., & FOMBRUN, C. (1979). SOCIAL NETWORK ANALYSIS FOR ORGANIZATIONS. ACADEMY OF MANAGEMENT REVIEW, 4(4), 507-519.

VAN DUIJN, M., & VERMUNT, J. (2006). WHAT IS SPECIAL ABOUT SOCIAL NETWORK ANALYSIS? METHODOLOGY: EUROPEAN JOURNAL OF RESEARCH METHODS FOR THE BEHAVIORAL AND SOCIAL SCIENCES, 2(1), 2-6.

REFERENCE LIST

WAGNER, C., & LEYDESDORFF, L. (2005). NETWORK STRUCTURE, SELF-ORGANIZATION, AND THE GROWTH OF INTERNATIONAL COLLABORATION IN SCIENCE. RESEARCH POLICY, 34(10), 1608-1618.

WASSERMAN, S., & FAUST, K. (1994). SOCIAL NETWORK ANALYSIS: METHODS AND APPLICATIONS: CAMBRIDGE UNIV PR.

ZHANG, P. (2006). MODEL AND EMPIRICAL STUDY ON SOME COLLABORATION NETWORKS. PHYSICA A: STATISTICAL MECHANICS AND ITS APPLICATIONS, 360(2), 599-616.

ZHOU, T., WANG, B., JIN, Y., HE, D., ZHANG, P., HE, Y., ET AL. (2007). MODELLING COLLABORATION NETWORKS BASED ON NONLINEAR PREFERENTIAL ATTACHMENT. INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 18(2), 297.

FURTHER REFERENCES

HTTP://CHADCHAE.HUBWEB.NET

HTTP:// CHADCHAE.HUBWEB.NET/WIKIMEDIA/

HTTP://CHADCHAE.HUBWEB.NET/WORDPRESS

THANK YOU FOR YOUR CONSIDERATION

hrd685 presentation interesting version

data collection data

form of social network

university data

collaboration network

mode data mode data2

ahrd proceeding papers

collaboration results

data processing objectives1

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