Comparing collaborative annotations on books between libraries and social community sites. A case study
| Pages | 178-195 |
| DOI | https://doi.org/10.1108/EL-09-2014-0171 |
| Published date | 04 April 2016 |
| Date | 04 April 2016 |
| Author | Dan Wu,Xiaomei Xu,Wenting Yu |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Comparing collaborative
annotations on books between
libraries and social community
sites
A case study
Dan Wu
School of Information Management, Wuhan University, Wuhan, China
Xiaomei Xu
Library, Zhejiang University of Water Resources and Electric Power,
Hangzhou, China, and
Wenting Yu
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose – Based on the study of overall situation of the tagging function in the provincial public
libraries and library of major colleges and universities, this paper aims to examine the difference of
tagging behaviour of its users in library and social community sites. The authors also want to
understand the causes of a variety of annotation behavior in social community sites and libraries.
Design/methodology/approach – The authors collected all system log data of tags, comments and
ratings users added in Wuhan University library, and then found the tags, comments and rating of
corresponding books in Douban. Then, the authors did questionnaire survey to the Wuhan University
students.
Findings – The authors found that the annotation service in the library is not perfect as that in social
community site. Enthusiasm of users annotating books in the library is far less high than that on the
social community sites. Lack of understanding of the annotation service is the main reason why users
are not concerned or do not use the tagging service. But users have the needs of the organization of
personal information in the library using tags.
Originality/value – This paper investigated the library users’ behavior in the using library OPAC
course and compared the difference of annotation behavior between library and social community site.
Keywords Academic libraries, Rating, Book tagging behavior, Comments, Social tags
Paper type Research paper
Introduction
Collaborative annotation, also known as social annotation, is the process by which web
users use keywords or other natural language text to categorize, describe, comment or
rate information resources online (Su et al., 2010). Through sharing the annotated
This article is supported by National Program for Support of Top-notch Young Professionals in
China.
The current issue and full text archive of this journal is available on Emerald Insight at:
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EL
34,2
178
Received 24 September 2014
Revised 26 January 2015
Accepted 26 February 2015
TheElectronic Library
Vol.34 No. 2, 2016
pp.178-195
©Emerald Group Publishing Limited
0264-0473
DOI 10.1108/EL-09-2014-0171
information resources, Web users can collaboratively organize and retrieve the
resources, obtain a more comprehensive and in-depth understanding of the resources
and create special interest groups around the resources (Zauder et al., 2007). Ever since
the launch of the social cataloguing site LibraryThing in 2005, collaborative annotations
on books have been increasingly popular on a variety of social community sites, such as
Shelfari and Goodreads (Zhuang and Wu, 2012). On these sites, the related collaborative
annotation activities include adding tags to books, commenting on books and providing
ratings for books. For libraries, there are two benets to expand and strengthen
collaborative annotation services. First, collaborative annotation is a new method of
information organization. Users can store bookmarks, add tags of their own choosing,
rate and comment on books and designate individual bookmarks as public or private.
Meanwhile, they can share the information by inviting others to view, comment, rate
and offer feedback. The fact that the same resource has been tagged by more users
allows for drawing connections between various users’ collections and mutually tagged
resources. The process thereby supports knowledge discovery, tag suggestion and
insight into resource popularity, as well as interests and trends of users and
communities (Zauder et al., 2007). Second, collaborative annotation is user-centred.
Thus, it can attract more users to participate actively and take advantages of library
Web sites. With a growing number of annotations, information that users retrieve by
tags and that libraries recommend to users can be more accurate. Libraries can use
collaborative annotation tools, applications and folksonomies to enrich their annotation
functions and expand traditional services.
Inspired by the success of collaborative annotations on social community sites,
libraries started to provide such functions on their systems too. For example, among the
surveyed 28 provincial public libraries and 112 academic libraries in China, it was found
that about half (50 per cent) of the public libraries have the commenting function, 36 per
cent have the rating function, but only 29 per cent have the tagging function. Some
libraries provide external links to online book-related sites, such as Douban, Google,
Baidu, Dangdang, Amazon, WorldCat, CNKI and so forth. Only seven libraries provided
tagging, commenting, rating and external links.
As collaborative annotation is relatively new in library services, few studies have
been conducted to examine collaborative annotations in libraries and library user
annotation behaviours. Therefore, this article is motivated to conduct a case study on
collaborative annotations in libraries and comparing them with those on social
community sites. This study focused on using Wuhan University Library (WHUL) as
one example from the library side and Douban as the other example from the social
community site side. The research methods used involved log analyses and survey via
questionnaires.
Literature review
Motivation for user tagging
Sen et al. (2006) proposed three factors that were likely to inuence how people applied
tags: people’s personal tendency to apply tags based on their past tagging behaviours,
community inuence of the tagging behaviour of other members and the tag selection
algorithm that chose which tags to display. Also, they summarized ve kinds of
motivations: self-expression, organizing, learning, nding and decision support.
Through the investigation of different systems, Hammond et al. (2005) divided user
179
Comparing
collaborative
annotations
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