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DREaM 2 event

Social Network Analysis exercise –
some initial findings.

        Dr. Louise Cooke, Dept. of Information Science,
                             Loughborough University
Knowledge & Expertise
Knowledge & Expertise:
       Gender
Female

Male
Knowledge & Expertise:
                Role
P = Public library practitioner
A = Academic Librarian
H = Health Sector Librarian
L= Other Sector Librarian
S = PhD Student
R = Academic or University Researcher
O = Other
Network Measures:
Knowledge & Expertise
 Overall density 0.1787
 No. of ties 238

 Avg. degree centrality 6.4324

 Highest out-degree centrality = 22

 Highest in-degree centrality = 30

 20 cliques
Prior Acquaintanceship
Prior Acquaintanceship:
         Gender
Female

Male
Prior Acquaintanceship:
                Role
P = Public library practitioner
A = Academic Librarian
H = Health Sector Librarian
L= Other Sector Librarian
S = PhD Student
R = Academic or University Researcher
O = Other
‘Others’

Those who selected ‘other’ as their
primary status, were mostly in either
very senior managerial roles, or in
consultancy roles. This tends to be
reflected in the centrality of their
network positions.
Network Measures: Prior
Acquaintanceship
 Overall density 0.19
 No. of ties 256

 Avg. degree centrality 6.9189

 Highest outdegree centrality = 36

 Highest indegree centrality = 25

 Cliques (minimum 3 nodes) = 27

 Cliques (minimum 4 nodes) = 18
Some initial thoughts on
findings
   Our acquaintanceship network is slightly more
    connected than our knowledge & expertise
    networks – this is not surprising
   Both networks have the capacity for
    improvement of connectivity
   In particular, there is scope for increasing the
    connections between established researchers
    and PhD students – this aligns well with the
    DREaM project aims.
LIS DREaM 2: Social Network Analysis Workshop Exercise Results

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LIS DREaM 2: Social Network Analysis Workshop Exercise Results

  • 1. DREaM 2 event Social Network Analysis exercise – some initial findings. Dr. Louise Cooke, Dept. of Information Science, Loughborough University
  • 3. Knowledge & Expertise: Gender Female Male
  • 4. Knowledge & Expertise: Role P = Public library practitioner A = Academic Librarian H = Health Sector Librarian L= Other Sector Librarian S = PhD Student R = Academic or University Researcher O = Other
  • 5. Network Measures: Knowledge & Expertise  Overall density 0.1787  No. of ties 238  Avg. degree centrality 6.4324  Highest out-degree centrality = 22  Highest in-degree centrality = 30  20 cliques
  • 7. Prior Acquaintanceship: Gender Female Male
  • 8. Prior Acquaintanceship: Role P = Public library practitioner A = Academic Librarian H = Health Sector Librarian L= Other Sector Librarian S = PhD Student R = Academic or University Researcher O = Other
  • 9. ‘Others’ Those who selected ‘other’ as their primary status, were mostly in either very senior managerial roles, or in consultancy roles. This tends to be reflected in the centrality of their network positions.
  • 10. Network Measures: Prior Acquaintanceship  Overall density 0.19  No. of ties 256  Avg. degree centrality 6.9189  Highest outdegree centrality = 36  Highest indegree centrality = 25  Cliques (minimum 3 nodes) = 27  Cliques (minimum 4 nodes) = 18
  • 11. Some initial thoughts on findings  Our acquaintanceship network is slightly more connected than our knowledge & expertise networks – this is not surprising  Both networks have the capacity for improvement of connectivity  In particular, there is scope for increasing the connections between established researchers and PhD students – this aligns well with the DREaM project aims.

Notas do Editor

  1. Introductory overview with interdisciplinary examples/perspective