=Paper=
{{Paper
|id=Vol-2816/short7
|storemode=property
|title=Labelling on Academic library Websites
|pdfUrl=https://ceur-ws.org/Vol-2816/short7.pdf
|volume=Vol-2816
|authors=Tanja Svarre
|dblpUrl=https://dblp.org/rec/conf/ircdl/Svarre21
}}
==Labelling on Academic library Websites==
https://ceur-ws.org/Vol-2816/short7.pdf
Labelling on Academic Library Websites
Tanja Svarre [0000-0002-5468-0406]
Aalborg University, 9000 Aalborg, Denmark
tanjasj@hum.aau.dk
Abstract. This paper studies labels on Danish academic library websites. Labels
are one amongst several elements that can support user interaction with library
websites and their related content and thus add to a reduction of the vocabulary
problem. A total of 2075 labels used on the websites of 21 academic libraries
with special obligations were analysed using a combination of content analysis
and clustering analysis. The findings show not only large variety in the use of
labels amongst the libraries but also a large concordance of labels used across
library domains and purposes. A cluster analysis of the labels reveals that some
libraries with similar purposes and functions also tend to be similar in their use
of labels, which indicates a shared terminology within domains, sectors and pur-
poses. The findings add to our understanding of the characteristics and variety of
recent labelling across libraries in the academic library sector.
Keywords: Academic libraries, Websites, Labelling
1 Introduction
Library websites increasingly serve as the point of contact between the library and its
users [1]. An academic library website represents the online portal to the many re-
sources, both digital and analogue, that are offered to students, researchers and other
users [2, 3]. Being able to locate relevant information on research library websites is
crucial for students, researchers and other users when approaching the library website.
Thus, the library website is the gateway to the online information and resources that are
necessary when acting within the academic world [4, 5].
Labelling is one of several elements that ensure the usability of academic library
websites [3]. It has previously been shown how terminology and labelling on library
websites challenge usability [3, 6–8]. The Danish National Statistics Office lists 22
Danish research libraries with special obligations. Most are connected to higher educa-
tion institutions, such as universities and university colleges. The remaining libraries
are associated with national museums for history and various aspects of the arts, except
for one, which serves as the national library of D enmark and a university library for
several universities across the country. The aim of this paper is to study the use of labels
on Danish academic library websites. It sheds light on the characteristics of academic
library labels and on how libraries differ in their use of labels in terms of communi-
cating with their users.
——————
Copyright © 2021 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0). This volume is
published and copyrighted by its editors. IRCDL 2021, February 18-19, 2021, Padua,
Italy.
2 Theory
Labelling is one of four systems within information architecture outlined by Morville,
Rosenfeld and Arango [9]. In web environments, labelling is used to represent under-
lying information and guide users towards relevant content. Labelling is considered a
representation of knowledge organising systems [9]. Thus, labelling follows the char-
acteristics of knowledge organising systems as being controlled or free [10], simple or
complex [11] and narrow or broad [12].
Users can experience a variety of challenges when interacting with an information
system. One of these is known as the vocabulary problem [13, 14]. The vocabulary
problem addresses how the same content can be described and identified in an endless
number of ways, depending on the user’s viewpoint. Several empirical studies of library
websites illustrate this phenomenon. For example, Dougan and Fulton [15], in their
usability study of an academic library website, found issues both with the specificity of
terms and general problems in understanding the website terminology. General confu-
sion in terms of terminology was also identified in Tidal’s [16] study of an academic
library website. Knowledge organising systems play an important role in reducing the
vocabulary problem and explicating the content that vocabulary represents, but, clearly,
they should be developed with an understanding of user terminology to support users
in their interaction with the websites and the content.
Morville et al. [9] distinguish between four types of labels: 1) contextual links, 2)
headings, 3) navigation system choices and 4) index terms. In this paper, the focus is
on navigation system elements, as the analysis is based on the labels extracted from the
websites under study.
3 Methodology
The Danish National Statistics Office lists 22 libraries as research libraries with special
responsibilities. We based the selection of libraries on the 2019 statistics. One library,
the Danish School of Media and Journalism Library, could not be crawled by the web
crawler due to technical issues. This left 21 libraries for the empirical part of this paper.
The libraries with abbreviations are listed in Table 1. To ensure the most extensive
versions of the websites, we used the Danish version for the current analysis. Most of
the websites offer English counterparts, but they usually contain limited information
compared to the Danish equivalents.
We collected the data on 3 September 2020. We used an open access web menu
crawler (http://webscompare.com/) to crawl the selected websites. The crawler scrapes
category labels using Xpath [17] on the basis of one or several web addresses entered
into the interface. The output is a csv file with a flat, alphabetical list of the labels found
on the websites. After the data collection, the data was cleaned and prepared for data
analysis. The scraper is not capable of handling Danish special letters (Æ, Ø, Å), which
are commonly used across the websites in this study, and it replaces the special letter
with a blank space. The blanks were therefore manually replaced with the correct spe-
cial letters.
The data analysis consisted of two elements. First, we carried out a quantitative con-
tent analysis of the web categories [18, 19], analysing per library the number of cate-
gories, the average length of categories and the average number of terms in the catego-
ries. Subsequently, we used the text analysis functionality of the analysis software
NVivo (version 12 Pro) (https://www.qsrinternational.com/nvivo-qualitative-data-
analysis-software/home) for analyses at the term level. Specifically, we used the word
frequency functionality and analysed the 1000 most frequent terms in the dataset. We
used grouping with synonyms to consider similar terms as one. The analysis was carried
out using the Danish language, and the most frequent categories were subsequently
translated into English for reporting in the current paper. Subsequently, we carried out
a cluster analysis on the basis of word similarity to identify similar libraries.
Table 1. Included libraries
Abbreviation Library name Type of library
AARCH Aarhus School of Architecture Library UNI
ABSAL University College Absalon Library UC
ARBMUS The Workers’ Museum Library OTHER
AUB Aalborg University Library UNI
CBS Copenhagen Business School Library UNI
CINEMA Danish Film Institute Library OTHER
DESMUS Design Museum Denmark Library OTHER
DIIS Danish Institute for International Studies Library OTHER
DKDM The Royal Danish Academy of Music Library UNI
DST Statistics Denmark Library OTHER
DTU Technical University of Denmark Library UNI
FB Royal Danish Defence Academy Library OTHER
KADK The Royal Danish Academy of Fine Arts Library UNI
KB The Danish Royal Library UNI/OTHER
PHB Copenhagen University College Library UC
POLAR Polar Library UNI
SDUB University of Southern Denmark Library UNI
UCLB UCL University College Library UC
UCNB UCN University College Library UC
UCSB University College South Denmark Library UC
VIAB VIA University College Library UC
Legend: The libraries are divided into three categories by purpose: UNI (serving a university or
university-like institution), UC (serving a university college) and OTHER (serving other types
of institutions like museums or organisations).
4 Results
The libraries included for analysis serve different purposes (Table 1). Six libraries qual-
ify as university college libraries, eight are located at universities or university-like in-
stitutions, and six libraries serve different organisations or museums. The Royal Library
has a role both as the national library of Denmark and the university library for several
Danish universities, resulting in two labels in the table: university library and other.
9
8
7
6
5
4
3 No
2 Yes
1
0
Figure 1. Number of libraries incorporated in the host institution website
Yes=incorporated; No=not incorporated
In many of the library cases, their organisational relations appear from the placement
of the library website in the web structure. All the UNI and OTHER libraries (14 of the
21 libraries) are incorporated into their host institution websites. The remaining seven
libraries, meaning all the UC libraries and the Danish Royal Library, have independent
websites with no institutional connection to their host organisation (Figure 1).
4.1 Term Distribution
Crawling the 21 research libraries, we found the distribution of categories that appears
in Table 2. The table shows a large variation in the number of labels on the library
websites and an average of 98.76 labels per website. A standard deviation of 84.97
illustrates the large variation between the libraries.
Table 2. Number of labels, average length of labels and average number of label terms
Mean Minimum Maximum Standard deviation
Number of labels 98.76 29 378 84.97
Length of labels (characters) 16.66 2 43 8.57
Number of terms 2.25 1 9 1.37
We used the independent sample T-test to test if the variation was related to whether
the library website is incorporated into the host organisation’s website or has its own
website. With no significant difference identified for the number of labels, the average
length of labels or the average number of terms in labels, this does not appear to be the
case.
4.2 Term Frequency
We used the term frequency functionality in NVivo to identify high-frequency terms in
the data set. The results of the analysis appear in Figure 2. “Search” and variations of
“Library” are the most frequent terms along with other library-related terms like “Ar-
chive”, “Books”, “Materials” and “Journals”. Another category of high-frequency
terms relates to the library as a service function. This category is exemplified by terms
like “Way” (representing street names and wayfinding in Danish), “Contact”, “Book-
ing”, and “Opening”, inviting users to use the library and library services like assistance
from a trained librarian. The organisational attachment of many of the libraries is also
reflected in the most frequent terms in labels. Here we see the university abbreviations
(“SDU”, “DTU” and “CBS”) and “Research”, “Education” and “Student”.
120
100
80
60
40
20
0
SDU
Way
Movie
Booking
Search
Books
Research
Contact
Journals
CBS
Denmark
Archive
Knowledge
Materials
Collaborate
Student
Education
News
Library
Statistics
Organization
Opening
DTU
Figure 2. Most frequent terms in labels
Furthermore, we analysed the number of libraries in which the high-frequency terms
occurred (Figure 3). This figure, to some extent, changes the impression of the most
frequent terms. As would be expected, the institution-specific terms only appear in the
related libraries, whereas general library-specific terms are used more generally across
the included libraries, with “Library”, “Search” and “Contact” as the most used terms.
25
20
15
10
5
0
Way
Booking
Search
Contact
Research
Journals
Movie
SDU
Denmark
CBS
Books
Materials
Collaborate
Knowledge
Archive
Education
Statistics
Library
Student
Organization
News
Opening
DTU
Figure 3. Number of libraries using the most frequent terms in labels
4.3 Cluster Analysis
We used the clustering functionality in NVivo to analyse the similarity between the
selected libraries. The results of the analysis appear in Figure 4, which illustrates the
two main clusters that evolved from the analysis.
Figure 4. Cluster analysis based on word frequency
The upper cluster consists of all the university college libraries in the population. It
is interesting to identify how the purpose and the target group of the library actually
influences the choice of terminology at these libraries. The lower and larger cluster
consists of a combination of university libraries and the category “other”. Here, the
picture is a bit more muddled than the upper cluster of the figure, but still some obser-
vations can be made. For instance, the Danish Film Institute (CINEMA) and the Design
Museum (DESMUS) libraries are so similar that they end up in the same cluster. If the
next level of the cluster is considered, they are also connected to another museum, the
Royal Danish Defence Academy Library (FB). Likewise, the Aarhus School of Archi-
tecture Library (AARCH) and the Royal Danish Academy of Fine Arts Library
(KADK), which amongst others are connected to architecture education in Copenha-
gen, are also so similar that they share a cluster in the figure.
5 Discussion and Concluding Remarks
Our analysis shows that the academic libraries with special obligations in Denmark
serve various institutions and purposes. They represent a large variation in their use of
labels, both in numbers and variety. Previous research has identified challenges with
library jargon on academic library websites [e.g. 16]. Considering the most frequent
labels used in the current study, the deliberate use of terminology does not appear to be
prevalent. However, users should be involved in further studies to obtain a deeper un-
derstanding of this issue.
The cluster analysis revealed that academic libraries with similar purposes also tend
to be similar in their use of labelling. Independent sample T-tests did not reveal that
this can be explained by whether the libraries are incorporated into their host institu-
tions’ websites and thereby have institution labels as part of their pool of labels. Instead,
it seems that the specific use of labels is similar, for instance, between university college
libraries, between some museum libraries and between the two Danish schools of ar-
chitecture. The findings indicate that the libraries in their labelling draw on a shared
terminology within their domains, which is a step towards reducing the vocabulary
problem in information interaction. Further studies with users within the specific do-
mains can further elaborate on how they understand and experience the vocabulary
problem within their domains.
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