Is there any efficient reading strategy when using text signals for navigation in a long document?

DOIhttps://doi.org/10.1108/LHT-11-2016-0143
Pages458-472
Date20 November 2017
Published date20 November 2017
AuthorQuan Lu,Qingjun Liu,Jing Chen,Ji Li
Is there any efficient reading
strategy when using text signals
for navigation in a long document?
Quan Lu and Qingjun Liu
The Center for the Studies of Information Resources,
School of Information Management, Wuhan University, Wuhan, China
Jing Chen
School of Information Management, Central China Normal University,
Wuhan, China, and
Ji Li
The Center for the Studies of Information Resources,
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose Since researchers have utilized text signals to develop a mass of within-document visualization
analysis tools for reading aid in a long document, there is an increasing need to study the relationship
between readersbehavior of using text signals for navigation and their reading performance in the tools.
The purpose of this paper is to combine the text signals using behavior and reading performance in two kinds
of analysis tools to verify their relationship and discover whether there is any efficient reading strategy when
using text signals to navigate a long document.
Design/methodology/approach The methodology is a case study. The authors reviewed related
literature first. After explaining the design ideas, interface and functions of THC-DAT and BOOKMARK,
which are two reading tools utilizing two main kinds of text signals, one utilizing topics and the other utilizing
headings for reading aid, a case study was presented to collect click data on the text signals of participants
and their reading effectiveness (score) and efficiency (time).
Findings The results confirm that the text signals using behavior for navigation has a significant impact
on reading efficiency and no impact on reading effectiveness in both BOOKMARK and THC-DAT.
The discrete degree of clicks behavior on text signals has an impact on reading efficiency. The using behavior
of different types of text signals has different impacts on reading efficiency.
Research limitations/implications Using text signals for navigation time evenly can help improve
reading efficiency. And a basic strategy suggested to readers is focusing on reducing their time to find
answers when using text signals for navigation in a long document. As to utilizing the two different kinds of
text signals, readers can have different strategies. Accordingly, personalized recommendation based on
interval of adjacent clicks will help to improve computer-aided reading tools.
Originality/value This paper combines the text signals using behavior for navigation and reading
performance in two kinds of visual analysis tools, studied the relationship between them and discovers some
efficient reading strategies when using text signals for navigation to read a long document.
Keywords Navigation, Long document, Reading effectiveness, Reading efficiency, Reading strategy,
Text signals
Paper type Research paper
1. Introduction
As digital reading becoming more and more popular, long documents arise in various
application domains including scientific articles, news stories, patents, judgments and
decisions reported in courts and tribunals, and speeches delivered by plenary sessions
(Tagarelli and Karypis, 2013). Long documents may have complex hierarchy structure.
Library Hi Tech
Vol. 35 No. 4, 2017
pp. 458-472
© Emerald PublishingLimited
0737-8831
DOI 10.1108/LHT-11-2016-0143
Received 30 November 2016
Revised 18 January 2017
Accepted 20 February 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0737-8831.htm
The authors received funding from the National Natural Science Foundation of China, Nos 71303089
and 71273195.
458
LHT
35,4

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT