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Editor's Notes
In our 15th issue of Usability News:
Usability News is distributed to about 6000 usability professionals, developers, managers, and researchers in over 60 countries. We welcome your feedback and comments. Contributions, suggestions, and submissions for future issues should be directed to barbara.chaparro@wichita.edu.
SURL Home Page: www.surl.org
Usability News: www.usabilitynews.org
Designing for usability: www.optimalweb.org
Perception of Fonts: Perceived Personality Traits and Uses
Summary: This study sought to determine if certain personalities and uses are associated with various fonts. Using an online survey, participants rated the personality of 20 fonts using 15 adjective pairs. In addition, participants viewed the same 20 fonts and selected which uses were most appropriate. Results suggested that personality traits are indeed attributed to fonts based on their design family (Serif, Sans-Serif, Modern, Monospace, Script/Funny) and are associated with appropriate uses. Implications of these results to the design of online materials and websites are discussed.
INTRODUCTION
Often credited with creating first impressions, fonts are typically classified according to unique typographical features (serif, sans serif, etc) and overall appearance. The combination of appearance and typographical features often lead graphic artists and typographers to describe typefaces using personality traits (“less cuddly, more assertive,” Berry, 2004). In a BBC audio program (Peacock, 2005), fonts were depicted as feminine and masculine, among other traits. Feminine fonts were described as fine, serifed, sleek, and elegant; masculine fonts were characterized as being blocky and bold.
Most empirical research concerning fonts focuses on the legibility or readability with little concern for the perceived personality of typefaces. Typographers and designers are often interested in the typeface personality or “typographic allusion” which refers to “the capacity of a typestyle to connote meaning over and above the primary meaning which is linguistically conveyed by words” (Lewis & Walker, 1989, p. 243).
Brumberger (2003) describes the Bauhaus school of design and their belief that the “content and purpose of the text should dictate the design – the form – of a document, and that form, including typography, should express the content just as the verbal text itself expresses content” (p. 207). Within communications research, many experts suggest that typefaces can convey mood, attitude, and tone while having a distinct persona based on the font’s unique features. Each document should be rendered in a font that connects the mood, purpose, intended audience, and context of the document.
While there are a few studies regarding the perceived personality of typefaces in printed text, there are virtually no similar studies regarding text presented onscreen. Similarly, little research has evaluated user perceptions of what fonts are appropriate for digital uses. With the increased use of the Internet and other forms of media, there is a mounting need to establish user perceptions of typeface persona and perceived uses for documents delivered in digital format.
Purpose
The purpose of this study was to determine whether or not participants consistently attribute personality traits to a variety of fonts presented onscreen. We also attempted to determine if participants associate fonts with particular onscreen uses.
METHOD
Participants
Participants completed the survey in two parts (personality and uses). A total of 561 participants completed Part A (Personality) of the survey, and 533 completed Part B (Uses). For both parts of the survey, 72% of participants were females and 28% were males. Approximately 60% of participants were full-time students; 45% of participants were in the 20-29 year old age group, and 20% were in the 30-39 year old group. Eighty-one percent of the participants reported visiting websites daily. Approximately 46% of respondents indicated they spend 2 to 6 hours per week reading on the Internet.
Materials and Procedure
An online survey was used to collect the data (http://www.shaikh.us/fontstudy/). PHP and mySQL were used to construct the survey to allow for randomization of stimuli. Participants were provided with a consent form online. The survey took approximately 40 minutes to complete and consisted of a demographic questionnaire followed by two parts. Part A asked participants to rate 20 font samples using 15 personality adjective pairs based on a 4-point Likert scale. In Part B participants viewed 20 font samples and indicated whether they would use the font for 25 different digital uses.
The 20 fonts used throughout the online survey are shown in Figure 1. The fonts chosen included samples of serif fonts (Cambria, Constantia, Times New Roman, & Georgia), sans serif (Calibri, Corbel, Candara, Arial, Verdana, & Century Gothic), scripted/fun fonts (Rage Italic, Gigi, Comic Sans, Kristen ITC & Monotype Corsiva), monospaced fonts (Consolas & Courier New), and display or modern fonts (Impact, Rockwell Extra Bold, and Agency FB). Cambria, Constantia, Corbel, Candara, Calibri, and Consolas are new ClearType fonts developed by Microsoft.
Figure 1. Twenty font samples were used in the online survey.
In Part A, the participants saw a randomized sample of text (provided as an image) that included the alphabet, numerals, and common symbols rendered in 14-point as shown in Figure 2. The 15 personality adjective pairs used in Part A are shown in Figure 3. Personality research, adjective lists, and pilot testing were used to determine the final 15 adjective pairs used in the survey.
Figure 2. Sample of the text seen in Part A to assess personality traits associated with the fonts. This sample shows the font Consolas.
Figure 3. Fifteen adjective pairs were used to assess perceived personality of fonts. The scores were based on a 4-point Likert scale as shown.
Images showing one of three pangrams and the digits 0-9 were used in Part B to assess perceived uses of the fonts. The following pangrams were used (1) The quick brown fox jumped over the lazy dog. (2) Amazingly few discotheques provide jukeboxes. (3) Whenever the black fox jumped the squirrel gazed suspiciously. Display of the pangrams was randomized. The pangrams and digits were shown in both 12-point and 24-point for each font as shown in Figure 4. In Part B, the participants were asked to indicate whether they would use a font or not by clicking a checkbox (yes) or leaving it unchecked (no). Table 1 provides the 25 uses assessed in Part Three. Participants were allowed to choose as many or as few uses as they felt were appropriate; participants could also choose the option, “I would not use this font for any purpose.”
Figure 4. Sample of pangrams and digits used in Part B to assess perceived uses of fonts. This sample shows the font Corbel.
Table 1. 25 uses were evaluated for each font.
|
Websites |
Documents |
Reading Material |
Correspondences |
School-Related |
Other |
|
Graphics/Logos |
Business |
eBooks |
|
Online Textbooks |
Scrapbooking |
|
Textual Content |
Technical |
Online Magazines |
Instant Messaging |
Assignments |
Brochures |
|
Advertisements |
Children’s |
Online
Scientific/ |
Letter/Memo |
Online Tests |
Computer Programming |
|
Headlines |
Math |
Online News Articles |
Electronic Greeting Card |
|
Spreadsheets |
|
|
|
Short Stories |
|
|
PowerPoint Presentation |
|
I would not use this font for any purpose. |
|||||
RESULTS
Personality Traits. The 15 personality traits were collapsed into a mean personality score for each font. Principle Components Factor Analysis with Varimax rotation was used to form factors with eigenvalues exceeding 1.0. Analyses of scree plots and eigenvalues resulted in 5 factors as shown in Table 2. Fonts that shared typographic features (serif, etc) grouped together; but further means analyses of personality traits indicated the font groups also shared common personality traits. The Sans Serif fonts did not score extremely high or low on any personality traits. The Serif fonts scored highest on traits such as Stable, Practical, Mature, and Formal. Fonts in the Script/Funny factor had the highest means for Youthful, Happy, Creative, Rebellious, Feminine, Casual, and Cuddly. Masculine, Assertive, Rude, Sad, and Coarse were most associated with the Modern Display fonts. The final group, Monospaced, had the highest means for Dull, Plain, Unimaginative, and Conforming.
Table 2. Five font factors. Fonts are listed in order of factor
loadings.
Specific Personality Traits. Table 3 shows the fonts rated the highest for each personality trait evaluated in the survey.
Table 3. Top 3 fonts for each personality adjective.
Uses. Data for the uses were analyzed using frequency analyses due to the dichotomous nature of the data. All uses except for computer programming had at least one font chosen as appropriate by 50% of the participants; 46% of participants chose TNR for computer programming. Approximately 28% of participants said they would not use Agency FB for any purpose listed. Over 20% of participants said they would not use any of the Modern Display fonts (Agency FB, Rockwell Extra Bold, and Impact).
The uses that had the highest consistency for individual fonts across participants are shown in Table 4.
Table 4. Uses with the highest consistency among participants. Percent saying “Yes, I would use this font.”
Table 5 presents the top three fonts for each of the uses
presented in the survey.
Table 5. The top three fonts for each use. The lowest scoring font is also presented ("Last").
Summary of Uses by Factor
Sans Serif Fonts. Users preferred Sans
Serif fonts for Website Text (62%), Email (60%), and Online Magazines (56%).
Sans Serif fonts were least preferred for Digital Scrapbooking (32%),
Computer Programming (34%), and Math Documents (36%).
Uses for Serif Fonts. Users preferred Serif fonts for Business Documents
(71%), Website Text (67%), and Online Magazines (63%). The three uses that
were least associated with Serif fonts were Scrapbooking (28%), Children’s
Documents (34%), and E-Greetings (38%).
Script/Funny Fonts. Digital Scrapbooking (61%), E-Greeting (60%), and Website Graphics (53%) were rated as the highest uses for this group of fonts. The Script/Funny fonts were not preferred for Computer Programming (2%), Scientific Documents (3%), Spreadsheets (3%), and Math Documents (3%).
Modern Display Fonts. The three uses rated the highest by users for Modern Display fonts were Website Graphics (47%), Website Headlines (44%) and Website Advertisements (44%). The uses least often chosen for this group were Online Tests (9%), E-Books (9%), Spreadsheets (10%), and Online Assignments (10%).
Monospaced Fonts. Users chose Technical Documents (45%), Computer Programming (40%), and Math Documents (40%) as the highest uses for Monospaced fonts. The uses receiving the fewest votes were Digital Scrapbooking (18%), E-Greeting (21%), and PowerPoint (22%).
DISCUSSION
The results from the online survey resemble previous research based on print samples. Users consistently attributed personalities to fonts displayed onscreen. The 20 fonts chosen for this survey resulted in five factors based on prevalent personality traits. The factors each contained fonts that were related by typographic features. The factors provide designers with some guidance in terms of which type of font is best suited to differing personality expressions. Such knowledge can be used to set the tone of online documents.
The factors found using the personality data were used to analyze the uses from Part B of the survey. Uses were summarized across the factors in order to provide designers with overall guidelines concerning the use of fonts. Sans Serif and Serif fonts were most likely to be appropriate for items that are typically read onscreen. Artistic elements and children’s documents were seen as appropriate uses for the Script/Funny fonts. Modern Display and Monospaced fonts were not particularly high on any use. The choices of fonts for uses can be seen as related to the personality of the fonts. The Script/Funny fonts scored high on Youthful, Casual, Attractive, and Elegant traits which are all related to Children’s Documents and artistic elements. The Serif and Sans Serif fonts were seen as more stable, practical, mature, and formal; the uses they are appropriate for fit these characteristics.
Acknowledgment: The authors would like to acknowledge Zach Zaccagni for programming and Jeremy Slocum for assistance with the initial survey design. This study was funded by a grant from the Advanced Reading Technology team at Microsoft Corporation.
REFERENCES
Berry, J.D. (2004). Now read this: The Microsoft ClearType font collection. Seattle, WA: Microsoft Corporation.
Brumberger, E. (2003). The Rhetoric of Typography: The Persona of Typeface and Text. Technical Communication, 50(2), 206-223.
Lewis, C., & Walker, P. (1989). Typographic influences on reading. British Journal of Psychology, 80, 241-257.
Peacock, I. (Speaker). (2005). From Arial to Wide Latin (Radio Broadcast). London: BBC Radio. (Available online: http://www.bbc.co.uk/radio4/science/fromarialtowidelatin.shtml)
Examining the Legibility of Two New ClearType Fonts
Summary: This article introduces six new ClearType fonts developed by Microsoft. Legibility of two of the serif fonts, Cambria and Constantia, is compared to the traditional serif font Times New Roman. Results show that the legibility, as measured by the number of correct identifications of briefly presented characters, was highest for the new font Cambria, followed by Constantia, and then Times New Roman. Old style digits, such as 0,1, and 2, used in Constantia resulted in confusion with the letters o, l, and z. Times New Roman symbols were confused with both letters and other symbols.
INTRODUCTION
The release of Microsoft Windows Vista later this year will include six new fonts. The new fonts include 3 sans serif fonts (Corbel, Candara, and Calibri), 2 serif fonts (Constantia and Cambria), and 1 monospaced font (Consolas). Samples of the new fonts are shown in Figure 1. These fonts are designed specifically to take advantage of Microsoft’s ClearType subpixel rendering technology that enhances text quality on LCD displays.1 Table 1 shows the intended uses of the new ClearType fonts (see Table 1.)
Figure 1. Six new ClearType fonts.
Table 1. Prescribed Uses for the New ClearType Font (Berry, 2004)
|
Font Name |
Designed for: |
|
Cambria |
Business documents, email, web design |
|
Constantia |
Book typesetting, email, web design, magazines |
|
Corbel |
Business documents, email, web design |
|
Candara |
Email, web design, magazines, informal settings |
|
Calibri |
Documents, email, web design, magazines |
|
Consolas |
Programming environment |
Given the anticipated prevalence of these fonts on the Web, we were interested in comparing the new fonts to some of the traditional fonts used today for business documents, email, and web sites. Previous SURL investigating user performance with different fonts on web pages have found few differences in reading efficiency or performance (Bernard, et al., 2002) for approximately 1000-word text passages. Reading performance tends to be a very robust measure and typically differences across fonts are not observed unless they differ substantially in appearance (e.g., Rage Italic vs Verdana.)
To compare the new ClearType fonts to traditional fonts, we used an objective measure of legibility. Participants were presented individual characters from each font at very short durations and asked to verbally identify the character. We examined the percent correct identification for each character for each of the new fonts along with two traditional fonts, Times New Roman and Verdana. This article reports the findings of the serif fonts only, Times New Roman, Cambria, and Constantia.
Times New Roman is currently the default font used in Microsoft Word and has been a standard for printed business documents. Cambria was designed to be the ‘new’ Times New Roman. It is described to “have very even spacing and proportions” and targeted for “on-screen reading and to look good when printed at small sizes” (Berry, 2004). Bosma, the designer of Cambria, refers to it as a “robust, all-purpose workhorse text face.” Constantia is a serif font that was designed “primarily for continuous text in both electronic and paper publishing" (Berry, 2004). The font uses a small x-height, long ascenders and descenders, and is said to be appropriate for use in electronic journals. Figure 2 shows a character set of the three serif fonts.
Figure 2. Examples of the three fonts examined in this study.
METHOD
Participants
Ten students (5 male, 5 female) between the ages of 18 and 35 from Wichita State University participated in the study.
Materials
The experiment was conducted using a Dell Pentium IV laptop with ClearType™ font rendering technology enabled. The screen resolution was 1400 x 1050 at 60 Hz refresh rate and 120 dpi resolution. A program written in Visual C# was used to display the characters in 8-point font size. A Dell Logitech mouse was used to start and stop trial sessions. The laptop screen was positioned at a 90° angle and the text was presented at eye-level for each participant. The laptop was positioned at a distance such that the characters subtended a visual angle of .14° (the x-height of each font’s “w” character was used to determine the appropriate distance for each font). Characters were displayed using an exposure time of 34ms and a blanking time of 1.5 seconds. Participants used a chinrest to stabilize the head and control the viewing distance from the monitor.
Twenty-six lowercase letters were used in combination with the digits 0 through 9 and 17 symbols frequently found in mathematical or scientific documents. Tinker’s (1928) study on the relative legibility of letters, numbers, and symbols provided guidance in symbol selection. The symbols used included the following: π σ ÷ = + Δ ? % ± √ ∑ $ # @ & ! ∞.
Procedure
The order of the fonts was randomized across participants. Five trials were completed for each font after an initial practice period. Participants were provided a sample of the symbols to study before beginning a set of trials with that font. Participants initiated each trial by pressing a START button. Each trial began with a dot (‘.’) followed by the random presentation of each character and ended with a dot (‘.’). Participants read each character name aloud and completed 230 trials per font.
Results
Table 2 shows overall performance by font. Cambria resulted in the highest average percent correct followed by Constantia and then Times New Roman. Legibility of all three fonts was best with the letter characters, followed by digits, and then symbols. Constantia had more errors with its digits and Times New Roman had more errors with its symbols. Table 2 also shows the percent of trials skipped for each font. A skipped trial was one that the participants simply could not identify the character at all. Times New Roman had the highest number of skipped trials.
Table 2. Percent Correct Character Identification by Font
|
FONT |
Total |
Digits |
Symbols |
Letters |
% Skips |
|
Cambria |
92.87 |
91.5 |
89.2 |
95.8 |
1.4 |
|
Constantia |
87.80 |
74.4 |
80.5 |
97.7 |
1.4 |
|
Times NR |
87.55 |
84.9 |
75.6 |
96.4 |
2.8 |
Further analysis of each font at the character level resulted in a series of confusion matrices. Table 3 shows a summary of the characters most confused for each font. Figures 2-4 show this data graphically in the form of a sunflower plot. In these graphs, only those characters confused more than 3 times are shown in the x and y axes. The characters presented are shown on the x-axis and the characters reported by participants are shown on the y-axis. The number of extensions, or ‘petals’, on each sunflower signifies the number of times a presented character was confused with another character. Each plot is segmented into nine sections signifying the type of character confusion (S = Symbol, N = Numbers, L = Letters). For example, SS denotes symbols confused with other symbols, NS are numbers confused with symbols, LS are letters confused with symbols and so on.
Constantia showed the most confusion between symbols and letters (SL) and numbers and letters (NL). Times New Roman showed the most confusion with symbols and other symbols (SS), symbols and letters (SL), and numbers and letters (NL). Confusion within Cambria was limited to the symbol ! and the letter l, the symbol ÷ and +, the symbol $ and s, and between the number 1 and the letter l. The higher number of skips among the symbols and digits with Times New Roman is also evident in Figure 4.
Table 3. Characters Confused Most by Font
Figure 2. Sunflower plot of character confusion for Cambria.
Figure 3. Sunflower plot of character confusion for Constantia.
Figure 4. Sunflower plot of character confusion for Times New Roman.
Table 4 shows the individual character sets that were most confused in each font along with the percent correct identification. The squareness of the exclamation point in Cambria made it appear more like the letter ‘l’ than the exclamation point in Constantia and Times New Roman. The use of the old style numbers (which tend to be smaller as shown in Figure 2) in Constantia appears to be responsible for confusion of the number 2 and the letter ‘z’ and the number 0 and the letter ‘o’. The small size of the $ in Constantia resulted in higher confusion with the letter ‘s’ than in Cambria or Times New Roman.
Table 4. Characters confused in one or more of the fonts.
DISCUSSION
This study sought to investigate and compare the legibility of two new ClearType fonts, Cambria and Constantia, to the traditional serif font Times New Roman. Results show the legibility, as measured by the number of correct identifications of briefly presented characters, was highest for the new font Cambria, followed by Constantia, and then Times New Roman. Percent correct identification was high for the letter characters for all three fonts. Old style digits, such as 0,1, and 2, used in Constantia resulted in confusion with the letters o, l, and z. Symbols, which were confused with both letters and other symbols, were the most confused characters in Times New Roman. Overall, the findings were positive for the new fonts.
While it has been advised that the legibility of individual characters is not predictive of overall readability of a font (Tinker, 1963), the method used in this study allowed us to identify those characters that may be confused with other characters in a given font. Contextual cues when reading text may override letter confusion; however, there are instances where single character confusion could be problematic. For example, users trying to remember username and passwords for online accounts may confuse some letter-number combinations, such as zero and the letter ‘o’. International zip codes, inventory part numbers, and other mixed character values may also be impacted by such confusion. In another example, character confusion may play a role in safety. In a recent near-accident, an air traffic controller was reported to misread character codes on his monitor and accidentally sent an aircraft to a wrong location (BBC News, 2002).
This article only reported the results of two of the 6 new ClearType fonts. Further investigation of the remaining fonts will be presented in the next issue of Usability News.
Acknowledgment: The authors would like to acknowledge Peter Samuelson for the C# programming and Ed Merkle, Ph.D. for assistance with the graphical sunflower plots. This study was funded by a grant from the Advanced Reading Technology team at Microsoft Corporation.
REFERENCES
BBC News (2002). Screens blamed for 'air blunders'. May 23, 2002. Retrieved February, 20, 2006, from http://news.bbc.co.uk/1/hi/uk/2003701.stm .
Bernard, M., Lida, B., Riley, S., Hackler, T., and Janzen, K. (2002) A Comparison of Online Fonts: Which Size and Type is Best? ../usabilitynews/41/onlinetext.htm
Berry, J.D. (2004). Now read this: The Microsoft ClearType font collection. Seattle, WA: Microsoft Corporation.
Tinker, M. (1963). Legibility of print. Ames, IA: Iowa State University Press.
Tinker, M. A. (1928). The relative legibility of the letters, the digits, and of certain mathematical signs. Journal of General Psychology, 1, 472-496.
[1] See http://www.microsoft.com/typography/ClearTypeInfo.mspx for more information on ClearType.
Where's the Search? Re-examining User Expectations of Web Objects
Summary: In 2001, Bernard determined that users were able to form a schema for the location of web objects on informational websites. The current study investigates whether users' expectations have changed since the 2001 study. Changes were found in the expected location of the site search engine, internal links, and advertisements.
INTRODUCTION
In 2001, Bernard conducted a survey to determine the expected location for a variety of web objects. The study split web users into novice and experienced groups and evaluated expected location for the following web objects: back to home link, internal links, external links, internal search engine, and advertisements. Based on his results, Bernard concluded that users do have a schema or mental model of where web objects should be located (see Usability News 3.1 for his results.) When mental models are consistent with user expectations, it is expected that the users are likely to be more satisfied with the site and are able to locate information quickly and efficiently.
Today, a larger, more diverse group of users access the internet on a regular basis. Technology has made many advances in the last 4 years in such areas as XML, XHTML, CSS, Java, JavaBeans, ASP, SQL, and other developing technologies (http://www.w3.org). In theory, such advances in technology on the back-end can affect the prototypical layout of web objects on the front-end. We wondered whether users' schemas change to keep up with the advances in technology. The purpose of this study was to determine if user expectations for locations of web objects have changed since 2001.
METHOD
Participants
Undergraduate psychology students (N=142; 50 males and 92 females) received course credit for completing a survey regarding the expected location of navigational elements commonly found on informational websites. The majority of the participants (68%) were 20 years old or younger. Most participants (82%) reported using the web for 4 years or longer. Fifty percent of participants indicated they use the web for 2-6 hours per week. Participants most often use the web for educational purposes and entertainment.
Procedure
A methodology similar to that used by Bernard (2001) was used. Users were presented with a demographics questionnaire followed by a page containing a depiction of a web browser window. The mock browser window consisted of five horizontal and five vertical grid squares on a white background. Participants received a set of color-coded stickers labeled “About Us,” “Site Search Engine,” “Internal Links,” “Advertisements,” and “Back to Home” cut to the size of the grid squares. The page contained operational definitions of each type of web object; participants were asked to place the stickers in the location (using any direction except diagonal) they expected the corresponding web object to normally be located on a basic informational website.
All stickers were presented in the same size, one square, to avoid any restrictions on placement. Pilot testing indicated participants had difficulty deciding whether internal links should be at the top, right, or bottom. Pilot participants felt like most websites repeat the internal links in the footer; for this reason, two stickers were included for the internal links. Pilot tests did not reveal the need for more than one sticker for the other objects evaluated.
RESULTS
Frequencies were calculated for each web object for the 25 grid squares (Figure 1). The percentages are represented by increasingly darker shades of blue (white is <1% and black is >33%) in Figures 2-6.
The figures reveal that most participants had an expected location for each of the presented web objects.
Figure 1. Scale representing percentage of users choosing the grid square for the web object location.
As shown in Figure 2, participants (44%) expected the “Back to Home” link to be in the upper left corner of the web page. Approximately 15% of the participants expected the “Back to Home” link to be in the center of the footer and 11% expected it to be in the left area of the footer as shown in Figure 2.
Figure 2. Expected Location of “Back to Home” link
Figure 3 reveals that participants expected the “Internal Links” to be located on the left side of the web page. Participants were given the option of using just one or both of the internal links stickers; 60% used both stickers.
Figure 3. Expected location of “Internal Links”
As shown in Figure 4, many participants expected for find the “Site Search Engine” to be located in the upper right corner of the web page or near the upper left corner.
Figure 4. Expected location of “Site Search Engine”
Participants expected advertisements to be located either at the center top or the right side of the web page as shown in Figure 5.
Figure 5. Expected location of “Advertisements”
Figure 6 indicates participants expected to find the “About Us” link in the footer area or the left side of the web page.
Figure 6. Expected location of “About Us” link
Comparison to Bernard (2001)
Home Link. Bernard (2001) found the expected location of the home link to be the top-left of the web page. The data collected in 2005 indicates participants still have this expectation. Bernard’s study revealed a fairly high percentage of participants also expected the home link to be located in the footer area of the web page. The 2005 study revealed a similar trend.
Internal Links. Participants in Bernard’s (2001) study overwhelming expected the internal links to be located on the left side of the web page. The current study finds a similar expectation among participants. However, the 2005 data showed a tendency for users to also choose locations along the top of the web page for internal links. Bernard’s 2001 study did not have any users choose the top of the web page for internal link location.
The location of internal links has likely been affected by the increased use of DHTML/JavaScript menus. The technology that is more prevalent today is more conducive to multi-level navigation being displayed across the top of the web page.
Site Search Engine. In the 2001 study conducted by Bernard, participants expected the site search engine to be located in the upper center of the web page. The 2001 study also showed a preference for the lower center section of the web page. The current study did not find this trend; participants expected the site search engine to be located in the top right corner or the top left corner of the web page.
Possibly, the results from the 2001 study are more reflective of search engine sites commonly used in the early 2000s such as Yahoo, Excite, and AltaVista. These sites often placed the text entry box for the search in the upper center section of the page.
Sites today are often database generated and often feature internal search engines. Google search functions are readily available for installation on sites today as well. The 2005 data indicates that users are more aware of the internal site search engines versus search sites.
Advertisements. The previous study by Bernard (2001) revealed that participants expected advertisements to be located in the upper area of the web page. Participants in the 2005 study showed a similar preference for the upper area of the web page. However, in the current study, participants were almost as likely to choose the right side of the web page for the location of advertisements.
As technology has changed over the past few years, so have advertisements. Ads in the early 2000s were not as likely to be floating or intrusive in nature as they are today. For example, ads used today may float in front of the user in the left or center area of the page and then minimize to the right side of the screen.
About Us Link. The previous study by Bernard did not evaluate the location of the About Us link. In the 2005 study, users reported the About Us link to be in the footer area of the page.
DISCUSSION
As technology changes the face of the internet, users' expectations seem to shift as well. The changes over the past few years have not been dramatic but reflect updates in technology and advertising schemes. With "Web 2.0" being the buzzword, all implications indicate that the layout of web pages will continue to evolve to take advantage of technology that allows for faster download and more relevant content. Further research on the expected placement of web objects with international audiences has also been conducted and will be discussed in future issues of Usability News.
References
Bernard, M (2001). Developing schemas for the location of common web objects. Usability News 3.1. http://psychology.wichita.edu/surl/usabilitynews/3W/Web_object.htm
Does the Intrusiveness of an Online Advertisement Influence User Recall and Recognition?
Summary: This study investigated the effect of the type (banner ad, pop-up ad and floating ad) and state (animated and non-animated) of online advertisements on recall and recognition of the advertisements. It was hypothesized that floating ads, pop-up ads, and animated ads would be easier to recall due to their intrusive nature. Results showed that participants in the pop-up ad and floating ad condition had better recall of the presence of the ad as well as better recognition. Animation did not significantly influence any of these measures.
INTRODUCTION
With the availability and familiarity of the Internet increasing steadily, e-commerce has become very popular over the past decade. Online advertising has been a key player in the success of ecommerce. Pricewaterhousecoopers (PWC) and Interactive Advertising Bureau (IAB) (2005) report that in the United States alone, online advertising revenues totaled just about $5.8 billion for the first two quarters of 2005, outgrowing the revenue collected in 2004 by 25.8 percent.
Berthon, Pitt and Watson (1996) describe advertising on the World Wide Web to be unique in that the consumer finds the marketer, unlike in most other media. McDonald (1997) points out that advertising is important for the economic health of the Web simply because of the lack of any other revenue generation sources. Interestingly, he also claims that online advertisements are not intrusive because unless the user is interested, the advertisements do not get clicked. This, however, is not true in the present context with the advent of animation and rich-media content in online advertisements.
There are several types of online advertisements. Floating ads (Figure 1) are seen to be the most intrusive in nature because, apart from being information dense, they obstruct the content of the webpage. Pop-up ads (Figure 2) also obstruct the content of the webpage but they are easier to get rid of by simply closing the pop-up window. Banner ads (Figure 3) can be considered the least intrusive in nature. Even though animation can make banner ads information dense, they do not obstruct the content of the webpage.
Figure 1. Floating Ad
Figure 2. Pop-up Ad
Figure 3. Banner Ad
*The weather images were used from Stardock’s ObjectDock.
http://www.stardock.com/products/objectdock/
Briggs and Hollis (1997), calculated the ‘clickthrough’ rate for measuring ad effectiveness. This rate is a simple ratio of the number of times an ad is clicked and the total number of times the ad appears. For example, if an ad on a site is clicked by 3 out of its 100 visitors, the clickthrough rate would be 3% (Techtarget, 2005). Nielsen (1997) argues that the clickthrough rates are so low that only 0.01% of the websites make economic gain from advertisement and that most of the time website users don’t click on the ads. Briggs and Hollis (1997) also do not consider clickthrough rate to be the sole predictor of possible “brand building” and they think that the solo use of clickthrough rate undervalues the Internet as an advertising medium.
One way to draw attention to an advertisement is through the use of animation. Bayles (2002) investigated whether animation increases recall and recognition of novel banner ads by increasing user awareness. She found that animation did not play a role in augmenting awareness of banner ads. She also found that even when the participants recalled and recognized the presence of animation on the banner ads, they did not associate it to the ads.
The current study investigated the effectiveness of banner ads, pop-up ads and floating ads in terms of ad recall and recognition. Ad animation state was also manipulated to see its impact on the recall and recognition of the ads. It was hypothesized that recall and recognition of floating ads and pop-up ads would be higher than that of banner ads due to their intrusive nature.
DESIGN
The type of ad (a banner ad, a pop-up ad, and a floating ad) and the state of the advertisement (animated and non-animated) were the two independent variables used in the study. Four dependent variables were measured for each group: (1) recall of the advertisement, (2) accuracy in recalling the state of the advertisement, (3) accuracy in recalling the location of the advertisement on the page, and (4) accuracy of recognition of the advertisement viewed.
METHOD
Participants
Sixty Wichita State University students were recruited for their voluntary participation in the study. There were 13 male (21.7%) and 47 female (78.3%) participants. Their ages ranged from 18 to 55.
Apparatus and Materials
The study used a Pentium 4 powered computer displaying at resolution of 1024 by 768 pixels on a 17” flat screen monitor. Microsoft’s Internet Explorer version 6.0 with Macromedia Flash plug-in version 7 was used. Six forms of identical-sized advertisements (static banner ad, animated banner ad, static pop-up ad, animated pop-up ad, static floating ad, and animated floating ad) were placed approximately one-fourth of the way from the top of the left-aligned pages. The structure and layout of all six pages type were identical in layout and content and differed only in the type and state of the advertisement. The advertisement was for a fictitious restaurant.
Procedure
A questionnaire was used to gather background information prior to the participation in the study. The participants were randomly assigned to one of six conditions (static banner ad, animated banner ad, static pop-up ad, animated pop-up ad, static floating ad, and animated floating ad) and were shown a web page that contained a weather glossary and the assigned advertisement for the restaurant. They were asked to complete six information search tasks on that page and record their answers on paper. This was done to allow for adequate exposure to the ad. Participants were lead to believe that the purpose of the study was to evaluate the usability of the webpage only. They were not told that they would have to recall any portion of the web page following the search tasks.
After the completion of the search tasks, the participants were asked to recall the type of the advertisement, animation state of the advertisement, and its content. They were then asked to identify the advertisements that they were presented from a page with five other distracter advertisements. Finally, they were asked to complete a satisfaction questionnaire regarding the web page and the advertisement they just viewed.
RESULTS
Recall
Results show that 71.6% (43 participants) were able to recall an advertisement on the webpage. About 20% (9 participants) of those who remembered seeing an ad correctly recalled what the content of the advertisement. Forty-five percent (9 participants) in the banner ad condition, 85% (17 participants) in the pop-up and floating ad conditions were able to recall seeing an advertisement. Two-thirds (20) of the participants who saw a static ad remembered seeing an ad, and 76.6% (23 participants) who saw an animated ad remembered seeing an ad. Chi-Square analysis revealed a significant relationship between recall and the type of ad viewed. [X2 (2, N=60) = 10.51; p < .05] However, animation had no effect in the recall of the ads [X2 (1, N=60) = 0.74; p > .05].
Animation Recall
About 53% of the 43 participants who recalled seeing an ad correctly recalled the animation state of the advertisement they saw. Of them, 11 participants who saw a static ad remembered the ad as static and 12 participants who saw an animated ad remembered the ad as animated. Chi-Square analysis revealed that there was no significant relationship between the animation state of the ad viewed and recall of the animation state of the ad. [X2 (1, N=43) = 0.03; p > .05] Also, the type of the ad did not have a significant relationship with the recall of the animation state of the ad. [X2 (2, N=43) = 4.59; p > .05].
Location Recall
About 74% (32 participants) of those who recalled seeing an ad correctly recalled the correct location of the advertisement. All but one person in the floating ad condition correctly recalled the location of the ad; 6 out of 9 participants who recalled seeing a banner ad remembered its location and 10 out of 17 participants who saw a pop-up ad recalled the location of the pop-up. Location recall was equal both for the animated and the static conditions.
Recognition
Seventy-three percent (44 participants) correctly recognized the ad from other distracters. Of those who saw the static ad, 70% (21 participants) picked out the correct ad in the recognition task, and 76.6% (23 participants) picked out the correct ad when the ad they saw was animated. Chi-Square results indicated no significant relationship between the recognition of the ad and the animation state of the ad viewed. [X2 (1, N=60) = 0.34; p > .05]. However, the type of the ad was significantly related to the recognition of the ad [X2 (2, N=60) = 12.44; p < .05].
Satisfaction
Animation had no impact on the recall or the recognition of the ad, however, when the participants were asked if the ad they saw bothered them, data showed that the participants who saw the animated ad reported being bothered more than those who saw the static ad [X2 (1, N=60) = 5.08; p < .05]. In addition, only 1 out of the 20 participants in the banner ad condition agreed that the ad bothered them whereas 10 participants in the float ad condition and 7 participants in the pop-up ad condition said they were bothered by the ad.
Table 1. Participant performance across the animation state of the ad.
|
|
|
STATIC |
ANIMATED |
TOTAL |
|
Saw an Ad? |
|
|
|
|
|
YES |
20 |
23 |
43 |
|
|
NO |
10 |
7 |
17 |
|
|
|
|
|
|
|
|
Correct recall of animation? |
YES |
11 |
12 |
23 |
|
NO |
9 |
11 |
20 |
|
|
|
|
|
|
|
|
Correct recall of location? |
YES |
16 |
16 |
32 |
|
NO |
4 |
7 |
11 |
|
|
|
|
|
|
|
|
Correct recognition of ad? |
YES |
21 |
23 |
44 |
|
NO |
9 |
7 |
16 |
|
|
|
|
|
|
|
|
Was the ad on the page bothering? |
YES |
5 |
13 |
18 |
|
NO |
25 |
17 |
42 |
Table 2. Participant performance across the type of the ad.
|
|
|
BANNER |
pop-up |
FLOAT |
TOTAL |
|
Saw an Ad? |
YES |
9 |
17 |
17 |
43 |
|
NO |
11 |
3 |
3 |
