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

TERMS


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

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REFERENCE LIST

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

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http://www.netminer.com/NetMiner/product_04.jsp




http://www.netminer.com/NetMiner/overview_01.jsp

http://www.netminer.com/NetMiner/overview_01.jsp

REFERENCE LIST

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

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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


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Hrd685 presentation interesting version