Impact of device on search pattern transitions. A comparative study based on large-scale library OPAC log data
| DOI | https://doi.org/10.1108/EL-10-2016-0239 |
| Published date | 07 August 2017 |
| Date | 07 August 2017 |
| Pages | 650-666 |
| Author | Dan Wu,Renmin Bi |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Impact of device on search
pattern transitions
A comparative study based on large-scale
library OPAC log data
Dan Wu and Renmin Bi
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose –This paper discusses the differences in search pattern transitions for mobile phone, tablet and
desktop devices by mining the transaction log data of a library online public access catalogue (OPAC). We
aimed to analyze the impacts of different devices on user search behavior and provide constructive
suggestions for the development of library OPACs on different devices.
Design/methodology/approach –Based on transaction logs which are 9 GB in size and contain
16,140,509 records of a university library OPAC, statistics and clustering were used to analyze the differences
in search pattern transitions on different devices in terms of two aspects: search eld transition patterns and
query reformulation patterns.
Findings –Search eld transition patterns are inuenced by the input function and user interfaces of
different devices. As reformulation times increase, the differences between query reformulation patterns
among different devices decrease.
Practical implications –Mobile-side libraries need to optimize user interfaces, for example by setting
web page labels and improving input capabilities. Desk-side libraries can add more suggestive content on the
interface.
Originality/value –Unlike previous studies, which have analyzed web search, this paper focuses on
library OPAC search. The search function of mobile phones, tablets and desktops were found to be asymptotic,
which was a good illustration of how devices have a large impact on user search behavior.
Keywords User interfaces, Information seeking behaviors, Transaction logs,
Library OPAC searches, Query reformulation, Search elds, Search patterns
Paper type Research paper
Introduction
A library, with its large amount of bibliographic and user behavior data, is an important
platform for the construction of Big Data resources. In the Big Data environment, the
effective management and utilization of library user behavior data can promote service
innovation for the library and improve social value and inuence. Based on analysis of
bibliographic data, libraries can play a role in information analysis and decision-making,
providing data support for government administration, scientic decision-making, scientic
research and so forth. Using an analysis of user behavior data, libraries can improve
personalized service and other information services. The study of user behavior using
library data has become a hot topic in recent years.
With the rapid development of the mobile Internet, increasing numbers of people are
using mobile devices, such as mobile phones, tablets and wearables, to access the web. The
This article is supported by the Project “Big Data Analysis of Library Users’ Behavior and Service
Innovation for Mobile Internet” supported by the Humanities and Social Sciences Fund of the Ministry
of Education in China (Grant No. 16YJA870009).
The current issue and full text archive of this journal is available on Emerald Insight at:
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EL
35,4
650
Received 31 October 2016
Revised 17 January 2017
Accepted 9 April 2017
TheElectronic Library
Vol.35 No. 4, 2017
pp.650-666
©Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-10-2016-0239
library online public access catalogue (OPAC), as the entrance for accessing library
resources, is also searched by users with different devices. In addition to searching directly
on the OPAC website, there are many other ways to access the library OPAC, especially for
mobile devices. For instance, some libraries have a library application (app) for mobile
devices and, in China, some libraries use a popular instant messaging app called WeChat to
provide access to the OPAC. The differences between the diverse devices and access
methods, such as the screen size, the input method and the user interface, may affect user
information-seeking behaviors and search results. Therefore, it is necessary to explore
whether differences exist when searching a library OPAC using different devices to improve
search efciency, especially for mobile devices.
Some comparative studies of mobile search and desktop search on the web have found
differences between different devices, such as the time spent, the number of inputs, the
number of clicks and the query length. Kim and Albers (2002) found that searching using a
mobile device took longer than using a desktop to complete the same task. Kamvar et al.
(2009) reported that desktop users had more queries per search session than mobile users.
The average input time and average character length were longer on mobile devices than
desktops, whereas the number of inputs was lower (Wu and Bi, 2016). Compared with web
searches of all kinds of information, library OPAC searches, on a small range of academic
information resources with high credibility, is more specic. Furthermore, search engines
provide a full-text search strategy, especially keywords search, whereas a library OPAC uses
a eld search strategy, especially the combination of search elds. Search elds, such as title,
subject and author appearing beside the search box, help users to clarify their information
demands and select appropriate query terms before query inputs. Thus, web search is
different from a library OPAC search. However, it is not known whether the differences in
impact that different devices have on library OPAC search are the same as those for web
search, and it is this issue that this paper explores.
Search eld selection and query reformulation are essential information-seeking
behaviors. Search eld transition patterns and query reformulation patterns reect the
process of constantly adjusting the search tactics and clarifying information demands. The
two search patterns may be inuenced by the use of different devices, given the different
device sizes, user interfaces, search functions, users’ habits and so on. Identifying the
differences in the two search pattern transitions on various devices can help libraries to
improve the search function on different devices and provide more accurate search services,
especially for the mobile-side library. This research study explores the differences between
search pattern transitions on different devices in OPAC search and compares the results with
web search. Two research questions are put forward:
RQ1. What differences are there in search eld transition patterns between different
devices searching on a library OPAC?
RQ2. How different are devices in accessing a library OPAC in query reformulation
patterns?
The two research questions were explored using large-scale transaction logs from a library
OPAC. The study required search session data containing durations, search elds and
queries performed by OPAC users. Log data are more objective and appropriate for
quantitative analysis than small-scale experiments or questionnaire investigations. Of
course, there are some limitations in using log data. For instance, the situation in which users
search and the emotions of users cannot be obtained from the log data, but the information is
essential for cause analysis.
651
Search pattern
transitions
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