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Network & Cluster Analysis of Departmental Libraries Used by Faculty at a Large University Library JoAnn Jacoby Associate Professor of Library Administration.

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Presentation on theme: "Network & Cluster Analysis of Departmental Libraries Used by Faculty at a Large University Library JoAnn Jacoby Associate Professor of Library Administration."— Presentation transcript:

1 Network & Cluster Analysis of Departmental Libraries Used by Faculty at a Large University Library JoAnn Jacoby Associate Professor of Library Administration and Anthropology & Sociology Subject Specialist Spiers Estate, South Africa 13-16 August 2007 7th Northumbria International Conference on Performance Measurement in Libraries & Information Services

2 Major research library – big collections (10 million vols.) & great librarians Decentralized library system (~40 libraries) Pressures catalyzing change User expectations multiplying & increasingly diverse Setting: University of Illinois Library

3 Purpose Map connections between departmental libraries from the users’ perspective Gain insight into the use of the ~40 libraries by faculty across disciplines Evaluate how the library’s structure might be changed to better serve faculty

4 Methods Mined data from survey of all faculty, academic professionals & staff, 2006 Responses to “Indicate your primary library/ (ies)” were used to create network maps and cluster trees –Respondents could choose as many libraries as they pleased

5 Response Rate *Distributed by a campus-mediated “massmail,” the survey was sent to 12,399 (not 13103) individuals because the headcount at the time was less than the annual maximum. The response rate was therefore slightly higher than shown.

6 Social Network Analysis Seeks to reveal the patterning of people's interaction (Roger Brown 1965) –Web of social connections key to understanding individuals, groups & societies Studies patterns in the relations social actors have with particular others (Grannis 2005) –Actors can be people, firms, nations, etc. –Relations = whether actors go to war, have sex, use a particular library, etc.

7 Methods Sociomatrix = Data for each relation presented in a two-way matrix, where the rows & columns refer to the actors making up the pairs. –Format used by most network analysis software –Adjacency matrix = type of sociomatrix used for dichotomous data (presence or absence of affiliation)

8 Methods Setting up the matrix

9 Methods Two-mode affiliation network 1st mode = 1350 faculty & staff respondents 2nd mode = 47 libraries “Connections among members of one of the modes are based on linkages established through the second mode” Affiliations and Overlapping Subgroups. In Social Network Analysis: Methods and Applications. Wasserman & Faust (1994). Cambridge University Press.

10 Methods Setting up the adjacency matrix- Quantifies the ties for the relation in question

11 Network map of connections among all libraries. Lines were drawn when >5 respondents reported using both libraries. Selected nodes are shown in color.

12 Software Packages International Network for Social Analysis (INSA), “Computer Programs for Social Network Analysis” –Comprehensive list of programs for data conversion, network analysis, data collection & project management

13 The INSA website -- a great resource

14 Pajek Free, well-documented, Windows software

15 TouchGraph Commercial source for software & consulting

16 BibApp Maps researchers & citations  'Institutional Bibliography'

17 Drawn by Hand in Adobe Illustrator (>20 only shown here)

18 Size classes by number of connections - Used natural breaks - Basis for circle size

19 Results Network maps were generated showing the connections among: –individual faculty maps –specific departmental libraries –groupings of related departmental libraries

20 Individual Respondents

21 Pink – Cinema Studies, Assistant Professor Indigo - Physics, Professor Green - Agricultural Science (ACES), Academic Professional Light Blue - Spanish, Italian & Portuguese, Associate Professor

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23 Specific Libraries

24 City Planning & Landscape Architecture Library

25 Modern Languages, English, Classics & Latin American

26 Health Science Library

27 Broad Disciplinary Groupings

28 All Divisions coded by color

29 Life Sciences Area StudiesArts & Humanities Physical Sciences & Engineering

30 Social Sciences Allied Special Collections Central Public Services

31 Mean Number of Libraries Used by Division

32 Cluster analysis of all libraries Confirms some patterns in the network maps, but is of limited utility in identifying potential mergers

33 Correlations with other indicators of activity level

34 Relationships between Number of Primary Library Designations, Circulation & Web Transactions

35 So what? Faculty don’t come in to the library anymore…. …if they can get what they need online …..right?

36 Comments: Library as Place I mostly use the library via online access…It's especially great when working at home or doing field research abroad Remote delivery of materials is a great service…as my duties make it challenging to get onto central campus to find a book. Your questions imply that we actually go to the library and want to interact with librarians

37 Effect of Online Library Resources by Status

38 Mode of Library Use by Status

39 Comments: Library as Place Person to person assistance can be key, especially when beginning new projects or trying to navigate through new search tools…. It would be easier to find print journals and books if the library was open more hours… The system of departmental libraries makes it very difficult for an interdisciplinary researcher to find and collect books s/he needs.

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41 Research into Practice ongoing decisions regarding the consolidation of library service points revealing areas of potential collaboration –e.g., the author collaborated with the Applied Health Sciences Library (alx) to create a health information portal after seeing evidence of a strong shared constituency

42 Conclusions Network maps and cluster trees: reveal connections and patterns in complex systems provide a data visualization tool that can help inform library decision- making

43 Conclusions Could be applied to other types of data: –co-locate/bundle suites of services frequently used or highly valued by certain groups of library users –create browsing collections (virtual or tangible) based on “people who checked this out, also checked out”

44 Questions?


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