Attention for Web Directory Advertisements: A Top-Down or Bottom-Up Process?

Abstract

Web directories have attracted many advertisers with their special advantages in their large user base. Until recently, attention mechanism of advertisements (ad) on web directories is not well understood. To investigate how the ad location and color of web directories influence users’ attention, this study uses eye tracking to measure the participants’ search time, total fixation duration and the location of the first fixation. Results reveal that visual attention on the ad area of a web directory is user-driven and follows a top-down process. The location of users’ first-fixations is the center of the screen. Ad links that place in the center area and on the top-left corner would increase users’ notice. Ad links that change color in the center area have the advantages of attracting user attention. Our findings suggest that ad links should be placed in the center area or on the top-left corner to increase users’ notice. Ad links placed in the center area should be designed using salient color to catch users’ visual attention.

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International Journal of Human–Computer Interaction
ISSN: 1044-7318 (Print) 1532-7590 (Online) Journal homepage: http://www.tandfonline.com/loi/hihc20
Attention for Web Directory Advertisements: A
Top-Down or Bottom-Up Process?
Yaqin Cao, Qingxing Qu, Vincent G. Duffy & Yi Ding
To cite this article: Yaqin Cao, Qingxing Qu, Vincent G. Duffy & Yi Ding (2018): Attention for
Web Directory Advertisements: A Top-Down or Bottom-Up Process?, International Journal of
Human–Computer Interaction, DOI: 10.1080/10447318.2018.1432162
To link to this article: https://doi.org/10.1080/10447318.2018.1432162
Published online: 02 Feb 2018.
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Attention for Web Directory Advertisements: A Top-Down or Bottom-Up Process?
Yaqin Cao
a
, Qingxing Qu
b
, Vincent G. Duffy
c
, and Yi Ding
a
a
Department of Industrial, School of Management Engineering, Anhui Polytechnic University, Wuhu, P.R. China;
b
School of Business Administration,
Northeastern University, Shenyang, P.R. China;
c
School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
ABSTRACT
Web directories have attracted many advertisers with their special advantages in their large user base.
Until recently, attention mechanism of advertisements (ad) on web directories is not well understood. To
investigate how the ad location and color of web directories influence users’attention, this study uses
eye tracking to measure the participants’search time, total fixation duration and the location of the first
fixation. Results reveal that visual attention on the ad area of a web directory is user-driven and follows a
top-down process. The location of users’first-fixations is the center of the screen. Ad links that place in
the center area and on the top-left corner would increase users’notice. Ad links that change color in the
center area have the advantages of attracting user attention. Our findings suggest that ad links should
be placed in the center area or on the top-left corner to increase users’notice. Ad links placed in the
center area should be designed using salient color to catch users’visual attention.
1. Introduction
A web directory is a directory on the World Wide Web
posting links to other websites and categorizes those links by
various topics, so they are easily found by inexperienced
internet users (Chung, 2012). For example, Yahoo had one
of the oldest and best Web directories on the Web
(Jachimczyk, Chrapek, & Chrapek, 2016). Web directories
are not only preferred by many internet users but also attract
lots of advertisers (Bilal & Wang, 2014; Chen, Magoulas, &
Dimakopoulos, 2005).
For internet users, web directories help them to quickly
locate relevant websites or to browse interesting yet unfami-
liar websites (Chung, 2012; Chung, Lai, Bonillas, Xi, & Chen,
2008; Chung & Noh, 2003; Yang & Lee, 2004). As the number
of the online website has been rapidly growing, a substantial
percentage of internet users use a web directory as entry
points to effectively locate or find a website (Ortiz-Cordova,
Yang, & Jansen, 2015). As of December 2015, according to
statistics from the China Internet Network Information
Center, the permeability of web directories was 56.7%
(China Internet Network Information Center, 2016).
The large user base of web directories attracts a number of
advertisers. Generally, advertisers want their ads attractive
enough to appeal more users, which in turn will increase the
fees the websites can charge for them (Aksakall, 2012; Ayanso
& Karimi, 2015). Advertising is the primary revenue stream for
those websites that provide directory services (Jacques, Perry, &
Kristensson, 2015; Jansen, Liu, Weaver, Campbell, & Gregg,
2011; Lee, Ha, Jung, & Lee, 2013; Vargiu, Giuliani, & Armano,
2013). The most dominant pricing scheme is pay-per-click
(PPC). Under this scheme, the advertisers pay a certain amount
to the websites for each users’click on the ad (Hu, Shin, &
Tang, 2015; Wu et al., 2013). Under the PPC pricing schemes, it
could not measure the effectiveness of ads until advertising
(Shen, 2002). In order to understand the effectiveness of ads
before they are shown, the advertisers should figure out the
important ad attributes that may influence users’attention. The
natures of ad design and ad location have been put forward as
critical factors (Resnick & Albert, 2014).
There are a body of studies exploring how those natures of
ad design, such as text only, picture, size, colors, etc., affected
a viewer’s attention to internet ads (Flores, Chen, & Ross,
2014; Hsieh & Chen, 2011; Li, Huang, & Bente, 2016; Lin &
Chen, 2009; Lohse & Rosen, 1999; Ryu, Lim, Tan, & Han,
2007; Yoo, Kim, & Stout, 2004). However, the results of those
researches are in conflict. For example, some studies have
found that salient stimuli have the function to increase
users’attention (Noiwan & Norcio, 2006; Yoo & Kim,
2005). In contrast, other studies show that salient stimuli are
not helpful to attract users’attention (Burke, Hornof, Nilsen,
& Gorman, 2005; Hsieh & Chen, 2011; Kuisma, Simola,
Uusitalo, & Öörni, 2010; Lee & Ahn, 2012).
In addition to the natures of ad design, ad location is
considered an important factor affecting users’attention
(Calisir & Karaali, 2008; Fox, Smith, Chaparro, & Shaikh,
2009; Jacques et al., 2015). In accord with Nielsen’s(2006),
‘F’-shaped webpage viewing pattern, Bernard (2001) also
found that banner ads are expected to be at the top of a
webpage. Did this location increase users’attention to the
ads? Kuisma et al. (2010) provided evidence that fewer
CONTACT Yi Ding emiledy@sina.com Department of Industrial, School of Management Engineering, Anhui Polytechnic University, Wuhu, 241000, P.R.
China.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/hihc.
INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION
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© 2018 Taylor & Francis Group, LLC

fixations landed on the banner ads at the top of the display
than the skyscraper ads on the right side. Using an eye-track-
ing experiment, Jiang, Li, He, Zhu, and Song (2009) found
that in web advertising, users’visual search response accuracy
descends from the central region to the four corners direction
of the screen. Simola, Kuisma, Oörni, Uusitalo, and Hyönä
(2011) reported that the animated ad presented in the periph-
ery attracted less attention than in the proximity of the text.
Simola, Kivikangas, Kuisma, and Krause (2013) demonstrated
that ads presented on the right captured more attention than
ads on the left. Resnick and Albert (2014) studied users’visual
attention for banner ad location and for a task type. A sig-
nificant finding of their research was that users paid less
attention to ad banners on the right side of the page in
goal-directed tasks. The results revealed that some of the
cognitive factors would influence users’attention to
online ads.
According to the theory of visual attention, two kinds of
factors affect attention mechanisms. One is a bottom-up fac-
tor; the other one is a top-down factor (Awh, Belopolsky, &
Theeuwes, 2012; Corbetta & Shulman, 2002; Itti, Koch, &
Niebur, 1998; Theeuwes, 2010). A bottom-up factor refers to
the stimulus itself, particular those salient stimuli (e.g., color,
motion). The individual’s‘mental set’can act as a top-down
factor (e.g., the mindset and motivation) (Ding, Guo, Zhang,
Qu, & Liu, 2016; Orquin & Lagerkvist, 2015; Theeuwes,
Reimann, & Mortier, 2007).
Another stream of studies on internet ad focuses on how
thosetop-downfactors,suchaspurpose,involvement,cog-
nitive style, affected a user’s attention to the ad. Kim and
Lee (2011) found that the exploratory search user would
pay more attention to the ad than the goal-directed search
user. Nettelhorst and Brannon (2012)havestudiedthe
effect of choice difficulty and users’need for cognition on
attention. Results showed that the ad attracted more atten-
tion after the low need for cognition individuals making the
difficult choice.
In addition to above two factors, the attention mechanism
of internet ad depends on the website in which it is embedded
(Calder, Malthouse, & Schaedel, 2009; Simola et al., 2013).
Different websites may affect ad viewing patterns differently.
Eye movements can provide finegrained information about
patterns of viewing ads (Higgins, Leinenger, & Rayner, 2014).
Eye-tracking is an accurate way of measuring eye movements
(Bang & Wojdynski, 2016; Guo, Ding, Liu, Liu, & Zhang,
2016; Rayner, 2009; Tardieu, Misdariis, Langlois, Gaillard, &
Lemercier, 2015). The use of eye-tracking in studying users’
visual attention is based on the assumption that users tend to
look at objects that they are thinking about (Just & Carpenter,
1976). Particularly, fixation duration and first fixation are the
most commonly used metrics to measure visual attention
allocation (Clifton et al., 2015; Just & Carpenter, 1976;
Rayner, 1998; Henderson, 2013). Fixation duration may indi-
cate the time to operate on visual information (Heuer &
Hallowell, 2015; Just & Carpenter, 1976; Wang, Yang, Liu,
Cao, & Ma, 2014). The first fixation has an important effect
on guide subsequent fixations (Laan, Hooge, Ridder,
Viergever, & Smeets, 2015; Manor, Gordon, & Touyz, 1995;
Peschel & Orquin, 2013).
Although eye tracking is becoming utilized in the ad
research, little is known about eye movement characteristics
when users are viewing the ad areas of a web directory.
The ad areas of web directories are unique from the ad areas
of the other websites. In the case of web directories, ad areas are
classified into different categories according to their topics.
Users expect to easily find a website name that matches with
their needs (Chen et al., 2005). In this context, the design of the
ad areas is a key factor that affects users’information search
performance, especially the accuracy and speed for locating a
specific website link (Chen et al., 2005; Näsänen, Karlsson, &
Ojanpää, 2001). In addition, the heterogeneous of users provide
a new challenge for the design of the ad areas on web directories
(Bar-Ilan & Belous, 2007; Gossen & Nürnberger, 2013).
According to the unique properties of web directories, as
well as the theory of visual attention, the following three
related research questions are generated:
Question 1: What are the mechanisms of visual attention
when users are viewing the ad area on a web directory?
Question 2: What are the eye movement characteristics when
users are viewing the ad area of a web directory?
Question 3: How did design factors of an ad on a web
directory affect users’attention to the ad?
This study aims to answer above questions using eye-track-
ing equipment, which can be used to measure users’visual
attention more accurately. This study is explorative, and
hypotheses were not proposed for two reasons: First, our
overall aim is to explore the visual attention mechanism
when users are viewing the ad area on a web directory,
which has not been discussed so far. We discuss this with
eye tracking method, which is rarely used in the context of
web directories. Second, the findings of effects of design
factors of an ad, such as the salient stimulus and the location,
on users’attention were mixed. This study will contribute to
understanding the effect of the ad color and location of web
directories on users’visual attention.
2. Method
2.1. Design
The study used a 2 (two common colors: black and red) × 5
(five typical positions: the top left corner, the top right corner,
the center area, the bottom left corner and the bottom right
corner) between-subjects full-factorial design. The colors
employed corresponded to two colors that were commonly
used in the ad area of web directories in China. Particularly,
most of the colors of the website links on web directories were
set to black. Only a few website links were set to red to add
emphasis. Five positions were selected as they were typical.
Ten unique webpages were obtained with these two features.
The design produced a total of 10 treatments, that is, the black
and top left corner (BTLC), the black and top right corner
(BTRC), the black and center area (BCA), the black and
bottom left corner (BBLC), the black and bottom right corner
2Y. CAO ET AL.

(BBRC), the red and top left corner (RTLC), the red and top
right corner (RTRC), the red and center area (RCA), the red
and bottom left corner (RBLC), the red and bottom right
corner (RBRC).
The dependent variables in the study were the participants’
performance and the location of the first fixation in the target
Area of Interest (AOI). The performance was measured by
search time and total fixation duration. Search time refers to
the total time spent looking for a given target link. Fixation
duration is defined as the total duration of fixations made in
the target AOI. The location of the first fixation is specified
using an (x, y) coordinate pair.
2.2. Participants
100 young Chinese adults (50 males; aging from 17–26 years,
M
age
= 21.17 years, SD
age
= 1.78) were the volunteers of the
experiment. They were all undergraduate students at a
Chinese University. All had normal or corrected-to-normal
vision. All reported being experienced with web directories.
Hao123.com was the most frequently used web directories by
participants. The detailed description of participants’demo-
graphic information is listed in Table 1. Participants were
individually tested at an Ergonomic lab. They were assigned
into one of 10 experimental conditions randomly after they
entered into the laboratory.
2.3. Stimuli
Ten mock webpages with a fictitious name were designed to
simulate the online searching process to isolate, control and
understand the impact of specific design elements on the depen-
dent variables. A fictitious name (Qiusuo.com) was designed to
avoid any potential bias from previous using experiences. The ad
area varied in locations and colors of a given target ad link
named Xisaiwang (http://www.educity.cn/). Xisaiwang was cho-
sen because participants were unfamiliar with it. Therefore, the
preexisting response bias was expected to minimize (Deng &
Poole, 2010).
The other design elements of the webpages were kept the
same. Especially, the color of the other ad links in the ad area
was black, which was the most commonly used color in real
web directories. The name of the other ad links consisted of
three Chinese characters.
For later analyses of the eye movements, the ad area was
defined as AOI. Example screen shots of the experiment
websites are shown in Figures 1 and 2.
2.4. Equipment
Stimulus presentation was controlled by an Acer
P229HQL display and viewed by the participants from a
distance of 60 cm from the screen. The resolution of the
display was 1920 × 1080. A Tobii X2-30 eye-tracker with
30 Hz sampling rate was used to collect ocular movement.
The eye tracking had 0.4° accuracy and 0.32° precision.
Its’freedom of head movement was 50 × 36 cm (Width ×
Height) at 70 cm away from the tracker. The operating
distance (eye tracker to the subject) was 40–90 cm. The
Tobii X2-30 was installed at the bottom of the display and
allowed binocular tracking.
2.5. Procedure
Participants were invited to a quiet and soft light room. Before
the experiment, the procedure was introduced, and demo-
graphic information of the participants was gathered. Before
the actual experiment, participants were asked to perform a
practice on a real web directory (https://123.sogou.com/). The
practice required participants to find out a specified website
name in the ad area, and click on the link as quickly as
possible once it was detected. For each participant, the website
name used in the practice was chosen according to a random
rule, which could avoid a significant influence of the practice
task on the first fixation location.
After completing the practice task, calibration was per-
formed and checked to guarantee the quality and precision
of the eye recordings. A five point calibration was adopted. If
the participant’s fixation point was fall into the corresponding
location of the calibration, the quality and precision of the eye
tracking system was guaranteed. Then, participants were
asked to perform the same task on the experimental websites.
The tasks required the participants to browse the ad area,
search for and click on the target ad link named Xisaiwang
as quickly as possible. Participants’searching time and eye
movements were recorded. A summarized description of the
procedure is given in Figure 3.
2.6. Data preprocessing and statistic analysis
Behavior and eye movement data were exported by using
ErgoLAB V2.0. Data missing because of software failure
were removed. Two participants’search time data and
four participants’eye movement data were not recorded
because of software failure, so six participants’data were
removed. A few outliers are sometimes enough to distort
group results (Cousineau & Chartier, 2010). Outliers of
the data were detected via the boxplot which was often
used in data preprocess (Guo, Cao, Ding, Liu, & Zhang,
2015). The dependent variable search time was used for
identifying the outliers. Four participants’data were
removed as outliers (Figure 4). As a result of these data
rejection, data from 90 participants were analyzed.
Table 1. Description of participants’demographic information.
Descriptive Frequency
Gender Female 50
Male 50
Age ≤19 15
20 23
21 25
22 15
≥23 22
The most frequently used web directories hao123.com 25
123.sogou.com 18
others 57
Eye-tracker experience Yes 0
No 100
INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION 3

According to Tabachnick and Fidell (2007) suggestion, the
removed data were replaced with the mean of the remain-
ing data of the corresponding group. SPSS 18.0 was used
for all analysis.
According to the method of Inal, Serteser, Coşkun, Ozpinar,
and Unsal (2010), the assumption of a normal distribution has
been violated with respect to some dependent variables. Log
transformation was used prior to statistical analysis.
Target link
Xisaiwang
Figure 2. Screen shot of one webpage (RCA) used for the experiment. AOI is framed in red.
Target link
Xisaiwang
Figure 1. Screen shot of one webpage (BTLC) used for the experiment. AOI is framed in red.
Instruction Questionnaire Practice Calibration Formal
Task
Figure 3. The procedure of experiment.
Figure 4. The box plots of search time.
4Y. CAO ET AL.

Univariate analysis of variance (ANOVA) was conducted
with both experimental factors (color and position) as
between-subject factors, and search time, total fixation dura-
tion and the location of the first fixation as dependent vari-
ables. An alpha level of 0.05 was used for statistical tests.
3. Results
Table 2 shows the means of all dependent variables for the 10
experimental groups.
3.1. Location of the first fixation
The mean and standard deviation of the location of first
fixation for xcoordinate is M= 889.44, SD = 13.92, for y
coordinate is M= 424.53, SD = 7.79 (Figures 5 and 6).
3.2. The effect of ad location
The analysis did not reveal a significant effect of ad location
on dependent variables except for the search time, F (4,
90) = 4.426, p= 0.003, η
2
= 0.164, total fixation duration, F
(4, 90) = 1.502, p= 0.208, η
2
= 0.063, and the location of first
fixation, for x, F (4, 90) = 1.523, p= 0.202, η
2
= 0.063, for y,F
(4, 90) = 0.805, p= 0.525, η
2
= 0.035. Further contrast tests
showed that the search time was significantly lower when the
target ad link on the top left corner (M= 6.89, SD = 1.42)
than on the top right corner (M= 9.66, SD = 1.51; p= 0.006)
and the bottom right corner (M= 9.33, SD = 1.16; p= 0.002).
The search time was significantly lower when the target ad
link on the center area (M= 5.63, SD = 0.62) than on the top
right corner (M= 9.66, SD = 1.51; p= 0.009) and the bottom
right corner (M= 9.33, SD = 1.16; p= 0.003). The search time
was significantly higher when the target ad link on the bottom
right corner (M= 9.33, SD = 1.16) than on the top left corner
(M= 6.89, SD = 1.42, p= 0.002) and the bottom left corner
(M= 6.67, SD = 1.16; p= 0.042) (Figure 7).
3.3. The effects of color
Regarding the search time as dependent variable, there was a
significant main effect for the color of the ad, F (1,
90) = 30.80, p< 0.001, η
2
= 0.255. Further contrast tests
showed that the target ad link in black (M= 5.13,
SD = 0.33) cost significantly less time than the red target ad
link (M= 10.14, SD = 0.53), p< 0.001.
As for the total fixation duration, results revealed a sign-
ificant main effect for the color of the ad, F (1, 90) = 19.35,
p< 0.001, η
2
= 0.177. Further contrast tests indicated that the
total fixation duration was significantly lower when target ad
link was black (M= 6.47, SD = 0.42) than the red one
(M= 10.92, SD = 0.81), p< 0.001 (Figure 8).
As for the location of first fixation, the analysis did not
reveal a significant effect of color of the ad on neither x
coordinate, F (1, 90) = 0.017, p= 0.897, η
2
= 0.000, nor y
coordinate, F (1, 90) = 2.182, p= 0.143, η
2
= 0.024.
3.4. The interaction effects of location and color
With regarding the location and color of the ad as independent
variables, the interaction effect for location and color of the ad
on the search time was significant, F (4, 90) = 5.961, p< 0.001,
η
2
= 0.209. As for the center area, the target ad link in black
(M= 6.11, SD = 1.31) cost more time than the red target ad link
(M= 5.14, SD = 1.31). However, the mean of the search time for
the other four positions was just the opposite: The target ad link
in black cost less time than the red.
With respect to the total fixation duration, the interaction
effect was not significant, F (4, 90) = 1.017, p= 0.403,
η
2
= 0.043 (Figure 9).
Considering the location of first fixation, the interaction
effect was not significant, for xcoordinate, F (4, 90) = 0.491,
p= 0.742, η
2
= 0.021, for ycoordinate, F (4, 77) = 0.851,
p= 0.497, η
2
= 0.036.
4. Discussion
The aim of the present study was to investigate the visual
attention mechanism when users are viewing the ad area on a
web directory. We recorded users’search time and eye move-
ments as indicators of how attention was allocated across the
different format of ads. Further, we analyzed how the location
and salient color of an ad on a web directory affect visual
attention.
The results revealed that the ad location and salient color
did not influence the location of the first fixation. The loca-
tion of users’first-fixations was the center of the screen. The
results indicate that the location of users’first-fixations on a
web directory is different from the results regarding webpages.
For example, Nielsen (2006) reported an ‘F’-shaped viewing
pattern with the first fixation on the left-hand side of a page.
Many studies of viewers’fixations on the results of web
searches showed that the first fixation was near the top of
the page (e.g., Pan et al., 2007). The conventional reading style
of people from most western cultures is viewing a page began
at the top-left corner with the first fixation on the top-left
corner (Scott & Hand, 2016). Interesting, the first fixation of
the ad area on a web directory was consistent with Rayner’s
(1998) statement that users initially direct their eye focus to
the center of displays. Our results indicated that inherent
perceptual biases, placing elements of importance near the
center, also existed in a web directory (Tosi, Mecacci, &
Pasquali, 1997).
Table 2. Means of all dependent variables.
Search time (s)
Total fixation
duration (s)
Location of the first fixation
(px)
xY
BTLC (2.92, 0.32) (6.45, 0.80) (922.72, 20.04) (421.43, 26.71)
BTRC (4.96, 0.60) (6.23, 1.03) (920.36, 54.70) (398.35, 50.94)
BCA (6.11, 0.72) (5.61, 0.67) (907.68, 35.90) (422.66, 15.22)
BBLC (5.08, 0.54) (6.54, 1.06) (825.97, 52.50) (412.87, 22.42)
BBRC (6.60, 0.93) (7.50, 1.10) (870.89, 68.35) (420.93, 16.13)
RTLC (10.86, 2.22) (10.42, 2.15) (871.10, 59.90) (477.51, 24.07)
RTRC (14.37, 2.09) (13.90, 2.00) (930.96, 40.60) (431.27, 11.12)
RCA (5.14, 1.03) (7.49, 1.32) (930.88, 38.81) (430.78, 21.49)
RBLC (8.26, 1.22) (10.00, 1.32) (854.46, 22.40) (420.59, 25.27)
RBRC (12.06, 1.77) (12.78, 1.68) (859.35, 23.66) (408.91, 11.41)
INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION 5

As for the effects of the ad location on attention, the results
showed that no significant effects of ad location on dependent
variables except for the search time. The search time was
significantly lower when the target ad link on the top left
corner than on the top right corner and the bottom right
corner. The search time was significantly higher when the
target ad link on the bottom right corner than on the top
left corner and the bottom left the corner. The results indicate
that the viewing strategy of the ad area on a web directory is
similar to the results regarding webpages. In general, users
browse webpages form top left to bottom right (Buscher,
Cutrell, & Morris, 2009). Ads placed in the ad area on a
web directory within this path would increase users’notice.
However, this finding was not consistent with previous
research on online ads, which have shown that people pay
less attention to ads place on the left or the top of the webpage
as compared with as placed on the right side of the webpage
(Goodrich, 2010; Kuisma et al., 2010; Simola et al., 2013,
2011). A possible explanation for the present results may be
that visual attention and viewing pattern change depending
on the unique nature of the ad used in the present study and
the type of the search task (Dumais, Buscher, & Cutrell, 2010;
Scott & Hand, 2016). In the case of ads on web directories,
users expect to easily find the ad, that is, a website name that
match with their needs (Chen et al., 2005). Users are likely to
browse the ad area form top left to bottom right as they
browse webpage. The search time was significantly lower
when the target ad link on the center area than on the top
right corner and the bottom right corner. The results also
support the viewpoints about the first fixation of the ad area
on a web directory was near the top of the page.
The findings of the salient stimulus’effects on the attention
of an ad were mixed. As for the effects of salient color on
attention, we found that salient color had significant effects on
Location
of the
first
fixation
Figure 5. Location of the first fixation.
Figure 6. Gaze plots of one group.
6.89
9.66
5.63 6.67
9.33
0
2
4
6
8
10
12
the top left
corner
the top
right
corner
the center
area
the bottom
left corner
the bottom
right
corner
Search time
Figure 7. The search time (mean) for the five positions.
6Y. CAO ET AL.

the participants’search time and total fixation duration. The
salient color was found to grab significantly longer search
time, and total fixation duration than less salient color. This
result indicates that salient color of an ad on a web directory
may affect visual attention and trigger suppression mechan-
isms that prevent eye-movements from going to the salient
color. This view is consistent with previous literature inter-
preting a goal-directed action as inhibition, in which salient
distractors produce less interference (Moher, Anderson, &
Song, 2015). An alternative explanation for this result is that
the surfer mode in the ad area on a web directory follows a
top-down process, in which visual attention is user-driven
(Bekkering & Neggers, 2002; Kaspar, Gameiro, & König,
2015). The fixed location of the first fixation also supported
the viewpoints above. Another possibility is that color is a
weak bottom-up signal for a web directory user. Therefore a
top-down modulation mechanism plays a role in the presence
of weak bottom-up signals (Corradi-Dell’Acqua, Fink, &
Weidner, 2015).
Finally, we examined the interaction effects of ad loca-
tion and color on participants’search time, total fixation
duration and the location of the first fixation. The interac-
tion effect on the search time was significant. The interac-
tions between location and color in this study suggested
that for the center area, salient color helped participants
search the target link quickly. The result suggests that users’
search performance were sensitive to a salient stimulus, the
color of the ads if they were placed in the center of the ads
area on a web directory. The results can be interpreted
according to users’first fixation on the ads. The location
of users’first-fixation was in the center area of the screen,
in which the salient color as a bottom-up effect tends to
operate in a short time (Donk & Zoest, 2008; Theeuwes,
2010;Van,Donk,&Theeuwes,2004).
However, there was no interaction effect on total fixation
duration. Participants’fixation behavior was inconsistent with
behavioral performance. The current pattern of the result is in
line with the view that users search the ads through a covert
process rather than overt fixations toward the ads (Burke
et al., 2005; Hong, Thong, & Tam, 2004; Simola et al., 2011).
Simola et al. (2011) demonstrated that covert processing of
ads occurs when an individual is exposed to ads in the
peripheral visual field. Our result indicates that covert atten-
tion to ads with salient color in the center area results in a
decrease in search time.
Therefore, based on the results, we demonstrate that visual
attention on the ad area of a web directory is user-driven and
follows a top-down process. The location of users’first-fixa-
tions was the center of the ad area. Ad location has significant
effects on users’search time. Ad links that place in the center
area and on the top-left corner would increase users’notice.
Ad links that change color in the center area have the advan-
tages of attracting user attention. We suggest that advertisers
should consider the users’visual attention and viewing pat-
tern when selecting the placement and format for a web
directory ad.
5. Conclusions
Understanding the visual attention mechanism when users
view the ad area on a web directory might provide additional
useful information to web directory operators and advertisers.
This study tested the impact of ad location and color on a web
directory on the users’visual attention via eye-tracking
equipment.
The results reveal that the visual attention on the ad area
on a web directory is user-driven and follows a top-down
5.13
10.14
6.47
10.92
0
2
4
6
8
10
12
black red
Search time (s)
Total fixation duration (s)
Figure 8. The search time and total fixation duration (mean) for the two colors of the target ad link.
2.92
4.96 6.11 5.08 6.6
10.86
14.37
5.14
8.25
12.06
0
5
10
15
20
the top left
corner
the top right
corner
the center
area
the bottom
left corner
the bottom
ri
g
ht corner
The search time (s)
Black
Red
Figure 9. The search time (mean) for the 10 experimental conditions.
INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION 7

process with the covert processing of ads. The location of
users’first-fixations is the center of the ad area. Ad links
that place in the center area and on the top-left corner
would increase users’notice. Ad links that change color in
the center area have the advantages of attracting user
attention.
The present study provides several additions to under-
stand the visual attention mechanism when users view the
ad area on a web directory and did provide two useful
implications for ad strategy. One stems from the results
that the visual attention on the ad area on a web directory
is user-driven and follows a top-down process. This result
indicates that the selection of ad location should consider
users’view strategy. Ad links should be placed in the
center area or on the top-left corner to increase users’
notice. The other strategy is suggested by the interaction
effectsofadlocationandcoloronusers’visual attention.
Our finds suggest that ad links placed in the center area
should be designed using salient color to catch users’
visual attention.
The present study is limited in several ways. First, we only
consider two common colors and five typical positions of the
ad. Many unexplored natures of ad design, such as the type of
ad (i.e., text only, picture, the combination of text and pic-
ture), the salient character of the ad (i.e., animation, the color
scheme), size of the ad, and other ad locations may affect
users’visual attention. Future studies can further test how
those factors impact users’visual attention. Second, only
experienced users of web directories were tested. It would be
interesting to compare visual attention between experience
users and inexperience users in the future. Third, although
100 participants took part in the study, only 10 participants
were assigned to each experimental condition. Future research
should consider increasing the sample size to examine the
robustness of the results.
Acknowledgments
This work was supported by the National Natural Science Foundation
of China [Grant no. 71701003, no. 71671001], by the Key Project for
Natural Science Fund of Colleges in Anhui Province [Grant no.
KJ2017A108], the General Project for Humanities and Social Science
of Higher Education Promotion Plan in Anhui Province [Grant no.
TSSK2016B27], and the Start Scientific Research Fund for Introduce
Talents of Anhui Polytecnic University [Grant no. 2016YQQ023, no.
2016YQQ007]. We thank all the participants for carrying out the
experiments. Further, we thank the editor and anonymous reviewers
for their valuable comments and advice.
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About the Authors
Yaqin Cao is an associate professor from the Department of Industrial
Engineering at Anhui Polytechnic University, Wuhu, China. She has
completed Ph.D. degree in Management Science and Engineering from
the Northeastern University, Shenyang, China. Her research interests
include Emotional Design, User Experience Design, and Human-
Computer Interaction. E-mail: caoyaqin.2007@163.com
Qing-Xing Qu is a Ph.D. student, in the Department of Industrial
Engineering, School of Business Administration, Northeastern
University, Shenyang, P.R. China. He was a visiting scholar at Purdue
University from Dec. 1, 2015, to Mar. 26, 2017. He obtained his Master
degree in Human Factors from Northeastern University in 2014. His
research interests include Human Factors, Kansei Engineering, User
Experience Design, Human-Computer Interaction, Human-Robot
Interaction and Smart Home System Design. Email: quqingxing@gmail.
com/yantaiquqingxing@163.com.
Vincent G. Duffy is an associate professor from the School of Industrial
Engineering at Purdue University. He obtained his Ph.D. in Human
Factors from Purdue University in 1996. Professor Duffy has been
chair or co-chair of twelve international conferences including four
International Conferences on Human Factors and Ergonomics in
Healthcare held jointly with Applied Human Factors and Ergonomics
International (AHFE). He was the chair for six conferences on Digital
Human Modeling and Applications in Health, Safety, Ergonomics and
Risk Management held as part of Human-Computer Interaction
International since 2007. His research interest includes Digital Human
Modeling, Safety Engineering, Work Methods and Measurement and
Ergonomics. Email: duffy@purdue.edu.
Yi Ding is a lecture from the Department of Industrial Engineering at
Anhui Polytechnic University, Wuhu, China. He has a Ph.D. degree in
Management Science and Engineering from the Northeastern University,
Shenyang, China. His main areas of interest and expertise are user
experience measurement and innovation, cognitive ergonomics and
development of quantitative and qualitative research methodologies for
examination of interaction with innovative products and information
systems, and mental workload. E-mail:emiledy@sina.com
10 Y. CAO ET AL.