How Facebook Users’ Perceptions of a Facebook Advertisement Affect Their Attitudes towards the...

Running Head: HOW FACEBOOK USERS’ PERCEPTION OF A FACEBOOK 1

How Facebook Users’ Perceptions of a Facebook Advertisement

Affect Their Attitudes towards the Brand in the Advertisement

Alexandra Holzworth, Abbey Miner, and Jay Springfield

University of Georgia

HOW FACEBOOK USERS’ PERCEPTION OF A FACEBOOK 2

Abstract

This article examines research done regarding how Facebook users’ perceptions of a particular

advertisement on Facebook affect their attitudes toward to the brand in the advertisement. It is

hypothesized that users with a positive perception of an ad will have a more positive attitude

towards the advertised brand. The variables of perception and attitude are conceptualized and

method for testing the research question is discussed. A statistical analysis test was run and it is

concluded that respondents have more favorable attitudes towards the advertised brand when the

perception of the ad is favorable, as well.


How Facebook Users’ Perceptions of a Facebook Advertisement

Affect Their Attitudes towards the Brand in the Advertisement

The explosion of social media that has occurred in the past five years has flipped the

advertising industry on its head, shifting the way products are being marketed and evaluated. For

example, in the past, advertising consisted only of one-way communication (Chi, 2011). Today,

advertising is much more interactive (Tan, Kwek, & Li, 2013). Advertisers must be a part of the

conversation now more than ever because consumers are placing much more weight on

recommendations by word of mouth than they are on paid television, print, and radio ads.

Facebook has been at the forefront of the social networking craze in that billions of consumers

are constantly posting on their Facebook ‘friends’’ walls, creating statuses, posting pictures and

sharing videos that provide feedback and product reviews (Hassan, Fatima, Akram, Abbas, &

Hasnain, 2013). For this reason, companies are eager to participate in Facebook dialogues about

their brand as much as possible. Not only do businesses now have the opportunity to create pages

and profiles for their brands, but they can also pay to have their product or service

advertisements show up in their target audiences’ and consumers’ newsfeeds (Hassan et al.,

2013). This advertising makes the consumers’ perceptions of Facebook advertising and the

attitudes towards those brands after viewing those ads more important today than they have ever

been.

Due to the importance of advertising today, advertising on Facebook and attitudes

towards advertised brands serve as the subjects of our research question, study, and hypotheses.

More specifically, our study focuses on how a Facebook users’ perception of a paid

advertisement put out by a specific brand’s company affects the consumer’s attitude regarding

that specific brand featured in the advertisement.


To break our two variables, “perception of a Facebook advertisement” and “attitude

towards the advertised brand” down even more, we attributed different dimensions to each

variable based on previous research. Our study is interested in finding out how the Facebook

advertisements’ relevance, trustworthiness, entertainment value, and informativeness affects

consumer action tendency, personal evaluation, and emotional feeling towards the brand as a

whole.

Though many studies on advertising and brand perception have been conducted before,

our study breaks new ground by analyzing a different combination of dimensions as well as a

separate, brand new method of advertising (Facebook advertising). Through a discussion of the

literature review, how our variables are conceptualized and the rationale leading to our

hypothesis, we seek to understand how consumer perception of Facebook advertising is related

to consumer attitude towards the advertised brand. Finally, in order to ensure that our

conclusions are valid and reliable, our study employs a survey method to test the hypothesis.

Literature Review

Many argue that ever since humans learned how to communicate, they have been

exploring the art of advertising. For centuries, advertising has been morphing to fit into evolving

communication mediums. One of the most prevalent channels for advertising today is the

internet. Now more than ever, businesses are using social media sites to market their products

and services (Tan et al., 2013). Due to social media’s growth in popularity, advertisers and

businesses have increased their investments in communicating with the consumers of social

networking sites (Chi, 2011).

Social media gives marketers the chance to get to know consumers on completely new,

more personalized levels because social networking sites provide consumers with an outlet to

express themselves and their interests through social connections (Chi, 2011). As a result, social


networking sites allow consumers to essentially “brand” themselves, making marketers more

aware of users’ likes, dislikes, and overall personalities. In addition, social media and social

networking sites give users more control over the information they put out and receive. Many

companies and businesses have realized the potential success in utilizing all of this stored data

and are taking action to reap the benefits (Tan et al., 2013). Advertisers use the information they

receive about consumers through social media sites to create and expose them to relevant

advertisements (Hassan et al., 2013). Facebook is a common example of a social networking site

that records the search terms, “likes”, and other information about its users to cater

advertisements in a way that is most effective (Hassan et al., 2013).

Based on the studies described, it is clear that advertising on social media has the

potential to be effective; however, there is still much to be discovered in regards to what makes

an ad effective from a branding standpoint. Most of the research performed on internet

advertising effectiveness in the past has been focused on the company’s point of view, instead of

the consumers’ (Schlosser, Shavitt, & Kanfer, 1999). Researchers, businesses, and advertisers

are all wondering how consumers’ (more specifically Facebook users’) different perceptions of a

particular Facebook advertisement color their attitudes towards the company’s brand.

Research Question

How does one’s perception of a particular Facebook advertisement affect his or her attitude

towards the advertised brand?

Conceptualizing Facebook Advertisements

This study will define Facebook advertisements as advertising that is owned by or paid

for by the company featured in the ad. Owned advertising means that the ad was put out

purposefully and directly by the company whose brand is being advertised. Furthermore, this

study will only consider advertisements that show up on the right hand side of a user’s Facebook


homepage, in their live feed in the upper right corner, or in their main newsfeed. These three

advertisement locations are the only ads being studied because they are consistently generated by

Facebook and other companies. Other ads that come from locations such as liked pages may hold

bias from the viewer since the subject was already previously liked.

Perception of a Facebook Advertisement

Since many different researchers have categorized the attributes of perception of

advertisements in various ways, our study will be modeled after categories from multiple sources,

breaking the attributes of perception of Facebook advertisements into relevance, trustworthiness,

entertainment value, and informativeness (Taylor, Lewin, & Strutton, 2011; Ling, Piew, & Chi,

2010; Kelly, Kerr, & Drennan, 2010).

Relevance

Relevance is how much an advertisement pertains to the general needs and wants of the

consumer. Facebook users have almost all of the control over what they see and all the control

over what they choose to pay attention to (Kelly et al., 2010). If an advertisement is not relevant

to the consumer and he/she chooses to ignore it, the advertisement will create either a negative or

uninfluenced perception of the advertisement.

Trustworthiness

Trustworthiness is another vital component when measuring Facebook users’ perception

of advertisements. In general, consumers already take caution when believing the contents of an

advertisement. Kelly et al. (2010) state that “studies report consumer distrust of advertising and

strong inclination towards advertising avoidance” (p. 16). If consumers do not believe the

advertisement is telling them the truth, they will have no desire to purchase the product.

Furthermore, they will be more likely to have a negative perception of the advertisement.


Entertainment Value

Though the trust built between a brand and consumer is vital to manifesting a positive

attitude towards the brand, the advertised messages must also be perceived as entertaining

(Taylor et al., 2011). Hassan et al. (2013) define entertaining advertisements as those that are

“fun, exciting, cool and flashy” (p. 321) and in most basic terms brings enjoyment to the viewer.

If Facebook users do not feel an advertisement is at least slightly entertaining, they will ignore

the advertiser’s message, which will not result in brand engagement with the consumer. Taylor et

al. (2011) describe how consumers may ignore or abandon a particular ad if they perceive it as

too commercial and not interesting enough. This research illustrates how users desire

entertainment in order to view ads in a positive light.

Informativeness

The last attribute of Facebook users’ perceptions towards Facebook advertisements that

we will be studying is informativeness. This dimension is especially important because as Kelly

et al. (2010) observe, many “perceive that products fail to perform as well as portrayed in

advertising and that the majority of advertising is more manipulative than informative” (p. 16). It

has also been suggested that one of the core functions of an advertisement is to make consumers

aware of product alternatives, thus enabling them to effectively make choices (Taylor et al.,

2011). The main goal of advertising is to provide information about products and services to

inform and persuade consumers. If the advertisement fails to inform, consumers remain

uneducated about the product/service.

Attitude towards Advertised Brand

In this study, the dependent variable is the attitude that consumers have towards a

particular advertised brand on Facebook. The attitudes that consumers form are based on how

likely they are to react in a favorable or unfavorable way while viewing a particular advertised


brand (Tan et al., 2013). Ling et al. (2010) recognize the attributes of attitude to be “individual

personal evaluation, emotional feeling attached and action tendency toward some objects or

ideas” (p. 116). Each attribute contributes to how this study will determine a Facebook user’s

attitude towards the specific brand being advertised on Facebook.

Action Tendency

The action tendency or behavioral intention describes what action the advertisement’s

viewers are inclined to take after seeing an ad. The action tendency indicates whether or not a

consumer has the desire to actually click the ad or purchase the item being advertised by a

particular company. Ling et al. (2010) claim that “Audience behaviour towards the advertising

can be indicated through consumers’ favourable or unfavourable response towards a particular

advertisement” (p. 116). A viewer’s perception of the ad can dictate what he/she will do in

response to looking at the particular brand advertisement. The persuasion that takes place to

sway the perception of a consumer can cause either a favorable or unfavorable reaction, resulting

in a changed attitude as a result of viewing a particular advertisement as evidenced by one’s

willingness to take action.

Personal Evaluation

Personal evaluation measures an individual’s association with a message that is based on

past experiences, preconceived notions, and personal beliefs to his/her attitude toward a specific

advertisement. More specifically personal evaluation as it relates to advertising consists of how

consumers assess certain brands using memories or perceptions that are completely unique to

them and their life encounters. According to Taylor et al. (2011), individuals are characterized by

their actions, so whether or a not a person clicks on a particular advertised brand depicts a sort of

self-identity for the individual. Taylor et al. (2011) describe that if an ad reflects an individual’s

self-identity, then the individual will be more likely to associate meaning to the ad, and in turn,


will be more likely to remember the ad. Brands that are associated with positive aspects of a

person’s life are going to be viewed in a more positive light by the consumer and vice versa.

Brands in advertisements that invoke the recollection of personal experiences are more likely to

stay with the consumers. Consequently, the company will build brand affinity with the consumer.

Emotional Feeling

The last attribute of attitude, emotional feeling towards a specific advertised brand, refers

to how an individual emotionally responds to the brand in an ad. According to Ling et al. (2010),

consumers’ attitudes towards advertising are highly influenced by their feelings towards each

particular advertisement. Likewise, the viewers’ attitudes towards the brand will alter based on

the emotion he/she experiences while viewing the ad. In this study, the emotional feeling

attribute will contribute to determining consumers’ attitudes towards a particular brand by

assessing any predispositions an individual may have towards a certain brand and the immediate

emotional responses individuals have towards the brand after viewing the ad.

Rationale

As discussed in the literature review, Facebook advertising is highly prevalent and

important today. When a Facebook user first encounters an ad, he/she has an initial response to

the ad and quickly views it through a certain lens. The perception of an ad is determined by

seeing whether or not the ad is relevant, trustworthy, entertaining, or informative, in which these

factors positively correlate to perception (Hassan et al., 2013). This perception of a particular

advertisement will, in turn, affect the attitude that the viewer has towards the brand being

advertised. Burns and Lutz (2006) propose that the correlation between perception of advertising

and attitude towards advertising is positive. It could be inferred then that the same relationship

holds for particular advertisements rather than advertising as a whole. Conversely, many studies

illustrate how negative perceptions of advertisements can lead to negative attitudes towards the


advertised brand (Taylor et al., 2011). According to Ling et al. (2010), informativeness,

trustworthiness, and entertainment value are all highly critical in producing a favorable

advertisement. Similarly, producing a favorable advertisement is necessary in order to create a

positive attitude towards the brand being advertised (Li, Edwards, & Lee, 2013). Relevancy is

also important in that most consumers do not actively search for advertisements to look at—

advertisers have the ability to cater their ads to the user, but they are typically viewed

involuntarily (Cheng, Blankson, Wang, & Chen, 2009). Since the ad is not being viewed

willingly, ads must be relevant in order to elicit a positive attitude, especially towards the brand

being advertised.

Despite the fact that most studies examine at attitude towards advertising in general

rather than towards the advertised brand, we are still able to gather information regarding brands

and attitudes and infer certain relationships. As mentioned earlier, attitude in this study is

composed of three attributes: action tendency, personal evaluation, and emotional feeling. By

studying these aspects of attitude, we are able to clearly see what attitude really is and how it is

affected by the perception of an ad. Tan et al. (2013) found that a consumer will “build up

emotional feeling of favourable or unfavourable manner towards the advertised brand” (p. 92) by

viewing an advertisement. In turn, if a consumer has a negative view of the ad, he/she will

experience an unfavorable emotional feeling as a result. Taylor et al. (2011) describe self-brand

congruity as consumers relating how they view themselves with how they feel about the brand in

the advertisement—the more positive they feel about themselves when viewing the ad, the more

likely they are to view the brand in a positive light. Self-brand congruity directly correlates to

perception of the ad as well—if the ad is more trustworthy or entertaining, then the viewer will

feel more positively about viewing the ad, thus viewing the brand more positively. Taylor et al.

(2011) illustrate this relationship between perception and attitude as a cost/benefit situation. If a


viewer perceives the ad to have more benefits than costs (the ad being more relevant, trustworthy,

entertaining, or informative), he/she will have a more positive attitude towards the ad. Based on

the support that has been outlined, we propose that:

H1: As one’s perception of a Facebook advertisement becomes more positive, one’s

attitude towards the advertised brand will also become more positive.

In order to see the relationship clearly, we must also look at how positive versus negative

perceptions of a Facebook ad affect the attitude that an individual has towards the advertised

brand. Research shows a clear positive correlation between the two variables; therefore, if

perception were to be more negative, then the attitude would in turn also be negative. Here we

would suggest that:

H2: Individuals with a negative perception of a Facebook ad will have a more negative

attitude towards the advertised brand than will individuals with a positive perception of a

Facebook ad.

Method

Participants

Eighty-five respondents (N = 66 females, 18 males; age: M = 21.64, SD = 7.66, range:

18-66) were acquired using non-probability convenience sampling through Facebook and e-mail.

Four respondents were excluded based on inability to complete the survey. The researchers

began with asking only University of Georgia undergraduate students to take the survey, but due

to lack of response, allowed people of all demographics (over the age of eighteen) to participate

in the study.

Procedures

The participants completed a questionnaire comprised of forty-three items regarding how

one’s perception of Facebook advertising affects his/her attitude towards the advertised brand.


All respondents were taken from the researchers’ Facebook friends and contacts on e-mail.

Participants were provided with a link to the survey to take it online using a computer/internet-

capable device of their choice. The estimated time for completing the survey was ten minutes.

Before completing the survey, participants electronically read and signed an informed consent

form disclosing all of the intentions of the study and what the participants should expect to see in

the survey. Since the survey was administered online, there was no in-person debriefing;

however, participants were provided the contact information of the researchers in case any

questions or concerns arose. Finally, all participants were thanked for taking time to participate

in the study.

A brief two-item introductory section of questions was included to allow respondents to

disclose their attitudes in general towards advertising on Facebook without having been exposed

to any further questioning. In this section, participants responded on a 5-point Likert-type scale

(1 = Strongly Disagree, 5 = Strongly Agree) to the statements “I like Facebook advertising” and

“I like to look at most advertisements that I am exposed to on Facebook.”

The last section of the questionnaire contained two Facebook advertisements taken from

a researcher’s Facebook page. Participants answered questions regarding the specific

advertisements. This section consisted of items that measure both the independent and dependent

variables. In the first half of this section, we displayed an ad for Verizon Wireless and asked

questions relating to perception of an advertisement and how it affects the attitude towards a

brand after immediate viewing (e.g. adapted from Ahn (2013), ‘I am more likely to view cell

phone service ads positively when I have preference for the brand’). The second ad was for Visa,

which contains an image of a person parasailing. This particular ad is used to see how people

respond to visually-detailed ads, posing statements like “While experiencing the ad, I feel as if I

were taking part in it” (Ahn, 2013). This section of the questionnaire was designed to see how


viewing a real ad affects both variables being measured. The questions were not in any order

based on variable, but were assigned to certain subgroups of each variable for the researchers to

use. Having participants view the ads in the survey and answer questions immediately was used

as an indicator of how participants’ perceptions of a certain Facebook ad affect his/her attitude

towards the brand, regardless of what the participant indicated earlier in the survey.

Independent Variable

Perception of a facebook advertisement. The independent variable assessing one’s

perception of Facebook advertising (n = 23) was measured on a 5-point Likert-type scale where

(1 = Strongly Disagree, 5 = Strongly Agree). The conceptualization of perception breaks this

variable down into four categories: relevance (n = 11, α = .802), trustworthiness (n = 3, α = .802),

entertainment value (n = 6, α = .895), and informativeness (n = 3, α = .918). Some items such as

“Advertising on Facebook supplies product information that is relevant to me” (Cheng et al.,

2009) in the relevance section were adapted from the original items in order to ensure clarity of

the variable being measured. Other items including “Facebook advertisements seem trustworthy”

(Ling et al., 2010) were altered in order to specify that the advertising comes from Facebook.

The responses to the survey items were added up and averaged to compare results. We used

IBM’s SPSS software to organize our data and collect the statistics for our study, showing

Chronbach’s Alpha to be α = .942 for the perception of a Facebook advertisement.

Relevance. This dimension of perception measured how relevant an ad on Facebook is to

the viewer. Statements such as “Advertising on Facebook supplies product information that is

relevant to me” (Cheng et al., 2009) were provided to determine the relevance of an ad. Only one

item in this section required reverse coding (‘Facebook ads do not have anything to do with me

or my needs’) from Lastovicka’s (1983) research. Lastovicka (1983) found the reliability for

advertising to be α = .846. Our measure’s reliability statistic was α = .802.


Trustworthiness. Trustworthiness looked at how trustworthy an ad appears to be to the

participants. We used items such as “I feel confident using information in a Facebook ad to help

me make a purchasing decision” (Schlosser et al., 1999) to measure trustworthiness. We found

that the measure’s reliability was α = .783. No sources directly measured trustworthiness;

however, Ling et al. (2010) looked at an advertisement’s credibility, finding the reliability

statistic to be α = .927.

Entertainment value. Entertainment value was used to determine whether or not the

viewer finds a particular ad on Facebook entertaining. An example of an item included is

“Facebook advertising usually has great entertainment value to me” (Cheng et al., 2009). The

reliability statistics for this subgroup of the study showed that α = .895, similar to Lastovicka’s

(1983) α = .872.

Informativeness. In this dimension of perception, we looked at how much information a

viewer thought was provided on any given advertisement. Statements such as “Facebook

advertising is a valuable source of information about the product” (Ling et al., 2010) measured

an advertisement’s informativeness for the viewer. We found the reliability of informativeness to

be α = .918, slightly higher than previous research done by Taylor et al. (2011) which found

Chronbach’s Alpha to be α = .87.

Dependent Variable

Attitude towards advertised brands. The dependent variable assessing one’s perception

of Facebook advertising (n = 18) was measured on a 5-point Likert-type scale (1 = Strongly

Disagree, 5 = Strongly Agree). Attitude was conceptualized into three different categories: action

tendency (n = 5, α = .915), personal evaluation (n = 7, α = .700), and emotional feeling (n = 6, α

= .756). No items in this section required reverse coding. Some questions, however, were

adapted in order to provide more clarity to the variable being measured. For example, Tan et al.


(2013) used the statement “After viewing online advertisements, I am more in love with the

advertised brand” in which we adapted to say “…I am more committed to the advertised brand”

in order to avoid extreme language. Other statements were altered to reflect attitude towards the

brand rather than just advertising. In one case, Cheng et al. (2009) posed “Advertising helps me

to know which products reflect my unique personality”; however, our survey uses “advertised

brands” instead of “advertising”.

Action tendency. For this attribute of the attitude towards the brand in the advertisement,

we looked at what viewers were likely to do after viewing the ad, whether it be clicking the ad,

purchasing from the brand, or ignoring the ad completely. We asked if respondents agreed to

statements such as “After viewing Facebook advertisement, I will purchase from the brand being

advertised” (Tan et al., 2013) to determine what action the viewer took regarding the advertised

brand. Tan et al. (2013) similarly studied purchase intention of products in an advertisement,

yielding Chronbach’s Alpha at α = .884. The reliability statistic of action tendency for this study

was α = .915.

Personal evaluation. For personal evaluation, we examined how different brands and

types of ads instill a deeper connection with users by utilizing their ability to connect with the

target market on a personal level. In other words, an advertisement that has been personally

evaluated in a positive manner probably reminded the user of a past experience, character, or

something else in their lives that they view with reverence. We measured this variable by asking

participants to agree or disagree with statements like “The brands advertised on Facebook are

consistent with how I see myself” (Taylor et al., 2011). While most of these items were highly

reliable, our group did have to reverse code two items to ensure that this variable’s reliability

was high enough to yield insightful results. These two statements read, “I feel that each brand of

cell phone service is relatively equal in quality” (Ahn, 2013) and “I feel that each brand of credit


cards is relatively equal in quality” (Ahn, 2013). The responses were recorded on a five-point,

Likert-type scale (1 = strongly disagree, 5 = strongly agree). However, even after reverse coding

these items, our reliability was not satisfactory, leading us to decide to exclude the two

statements from our analysis all together. When these two items were taken out, the reliability

statistic was then found to be α = .700. We compared the realiability statistic with a previous

study conducted by Taylor et al. (2011) that found the reliability statistic for personal evaluation

(named self-brand congruity) to be α = .900.

Emotional feeling. In this section, we measured what immediate emotional feeling a

viewer has towards the advertised brand. For example, we asked respondents to agree or disagree

with statements such as “After viewing online advertisements, I am more committed to the

advertised brand” (Tan et. al., 2013). Ling et al. (2010) looked at the hedonic pleasure that

viewers get from viewing an ad. Though it is not the exact same measure, hedonic pleasure and

emotional feeling are similar enough to compare reliability statistics. Ling et al. (2010) had a

Chronbach’s Alpha of α = .851 while our study had an Alpha of α = .756 for emotional feeling.

Results

Perception of Advertisement and Attitude towards Advertised Brand

The first hypothesis was one of covariation, which supposed that as one’s perception of a

Facebook advertisement becomes more positive, one’s attitude towards the advertised brand will

become more positive, as well. A one-way ANOVA test was used in order to test our first

hypothesis. This hypothesis tested the variables on a ratio level, comparing the actual numbers of

the responses. The results indicate that there was a significant relationship between the two

variables (Pearson correlation = .86, p < .001). Based on the high Pearson correlation and low p-

value, this hypothesis was supported.


The second hypothesis advanced the same idea as the first, except to the opposite effect,

stating that individuals with a negative perception of a Facebook ad will have a more negative

attitude towards the advertised brand than will the individuals with a positive perception of a

Facebook ad. For this hypothesis, we transformed perception to be a nominal level variable by

using a median split. We then placed the median of the perception averages in the low group

(splitting the perception responses from 1 - 2.32 and 2.33 - 5) because we found that the

distribution of respondents was more even (negative perception n = 39, positive perception n =

38) than when we placed the median in the high group (perception responses from 1 - 2.31 and

2.32 - 5). The results indicate that there was a significant difference in attitude toward the

advertised brand according to perception of Facebook advertisements (F (1,72) = 38.63, p <.001)

such that those with a negative perception of the Facebook ad (M = 2.14, SD = .44) had a

significantly lower attitude toward the advertised brand than those with a positive perception of

the advertisement (M = 2.91, SD = .62). Based on the positive correlation between the two

variables and the low p-value, there is a minimal possibility of the two variables being related by

mere coincidence and our hypotheses are supported.

Discussion

Due to the rise in not only social media usage, but also in paid advertising on these sites

and applications, we focused our study on how one’s perception of a particular advertisement

would affect his/her attitude towards the brand in the advertisement. As a general conclusion,

perception of a Facebook advertisement was positively correlated to the attitude towards the

advertised brand. With perception broken into four determining categories (relevance,

trustworthiness, entertainment value, and informativeness) and attitude into three categories

(action tendency, personal evaluation, and emotional feeling), all dimensions indicated a positive

correlation between perception of the advertisement and attitude towards the advertised brand.


Perception of Advertisement and Attitude towards Advertised Brand

This study explored how an individual’s perception of a particular advertisement seen on

Facebook would affect his/her attitude towards the brand in the advertisement. We predicted that

the perception of the advertisement and the attitude towards the advertised brand would have a

positive correlation and the results provided support for this hypothesis.

The perception of an advertisement was broken down into relevance, trustworthiness,

entertainment value, and informativeness, all of which accurately represented the make-up of

perception in this study. Attitude towards the advertised brand was comprised of three categories

(action tendency, personal evaluation, and emotional feeling). Since perception and attitude are

highly complex variables, they needed more specific dimensions to determine what was meant

when studying the variables and whether or not the relationship actually existed. The dimensions

for both perception and attitude all proved to strongly contribute to the correlation of the two

variables. Taylor et al. (2011) found that if a user perceived a social network advertisement

negatively, then he/she would in turn have a negative attitude towards the advertisement. Hassan

et al. (2013) describe how entertainment and informativeness in an advertisement contribute to

the positive attitude towards the brand, explaining that “It also encourages them to participate in

a virtual community” (p. 321). Facebook users have many different motives for using Facebook,

none of which are to look at advertising. However, when a company can create an ad that is

relevant, trustworthy, entertaining, and informative, they are able to receive a positive perception

of the ad and, in turn, a positive attitude towards the brand in the advertisement.

Limitations

With every research study comes limitations, and ours is no exception. One of the most

prominent restrictions on our study was the lack of time we had to conduct it. This study took

place over the course of less than four months, making it difficult to efficiently and effectively


gather and analyze results. With the constraint came limitations on the sampling method. Our

research obtained respondents by using a non-probability snowball sampling method and as a

result, our data was skewed in regards to gender, age, and personality. Most of the people that

took our survey were friends, family, or classmates of the researchers and many of them were

female. Finally, though this study originally set out to examine the behavior of University of

Georgia undergraduate students, lack of time and respondents resulted in an age group ranging

from under eighteen to over sixty.

Other limitations that are separate from the time constraint issue include the possibility

that (1) some of our participants have pop-up blockers on their computers, (2) no other previous

studies have been conducted regarding this specific topic, (3) there was a lack of ability to

measure every dimension of both perception and attitude, and (4) there was an absence of access

to social media advertising analytics. In order to elaborate on the first point, it is important to

note that each respondent was asked preliminary questions about their past experiences seeing

advertisements on Facebook in the survey. Since it is possible that some participants had never

seen a paid advertisement in their Facebook newsfeed or that participants that do have pop-up

blocker had a slightly different advertising experience than those who do not have the blocker,

our research data could have been skewed. It is difficult to assess this discrepancy because little

to no in-depth research on perceptions of and attitudes towards Facebook advertisements is

available to the general public.

Not many studies have focused specifically on this particular topic, but rather on the topic

of perceptions and attitudes of traditional advertising and advertising in general. These sources

indicated the complexity of attitude and perception, making it evident that one of our study’s

limitations would be the failure to include all the dimensions of each of the two concepts. Just as

it was impossible for our research to measure every aspect of attitude and perception, it was


difficult for us to measure the big data associated with Facebook advertising and its real world

results. In this study, we did not look at how many times an advertisement led to a sale, how

many people it reached, or how often they clicked through to the brand website. Though there is

software and multiple methods of measuring digital data, we were unable to access and process

this information for this particular study.

Future Research

As a result of our study’s vast amount of limitations, our research leaves others with

incredible opportunities for future studies. One interesting question that could be answered is

how effective is advertising on other social networking sites such as Twitter and Instagram? As

the digital age continues to expand, research regarding online behavior as well as perception and

attitude towards digital advertising will become nothing short of necessary.

As the social media field grows, so will its users. Now many different age groups

including baby boomers, generation X, and the multi-millennial have a strong presence on

various social media. It would be interesting to look closely at how age plays a role in perception

and attitude of online advertising. Another niche study could also look into different types of

digital advertising such as paid and nonpaid. Future research regarding the existing

personalization algorithms needs to be conducted in order to discover whether or not these ads

that are products of algorithms used to personalize the consumer experience are effective or

invasive.

Conclusion

Social media has taken flight in the past decade and advertising is prevalent on every

form. Facebook has particularly become wildly popular, appealing to companies as a prime

advertising medium. Due to the high usage of social media and the high levels of advertising on

these media forms, we decided to look at how one’s perception of an advertisement would affect


his/her attitude towards the brand in the ad. Based on analysis results and the administered

survey, it was concluded that perception of an advertisement and attitude towards the advertised

brand are closely and positively correlated. There is no limit to constrictions of this research

study or the amount of future research that could and should be conducted. However, this

examination of user perceptions of Facebook advertisements and their resulting attitudes towards

the advertised brand provides a basis for more in-depth results, knowledge, and insight.


References

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and Public Relations, University of Georgia, Athens, Georgia.

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Cheng, J., Blankson, C., Wang, E., & Chen, L. (2009). Consumer attitudes and interactive digital

advertising. International Journal of Advertising, 28(3), 501-525.

Chi, H. H. (2011). Interactive digital advertising vs. virtual brand community: exploratory study

of user motivation and social media marketing responses in Taiwan. Journal of

Interactive Advertising, 12(1), 44-61.

Hassan, M. U., Fatima, S., Akram, A., Abbas, J., & Hasnain, A. (2013). Determinants of

consumer attitude towards social-networking sites advertisement: testing the mediating

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scales. Journal of Advertising, 12(2), 14-52.

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Ling, K. C., Piew, T. H., & Chai, L. T. (2010). The determinants of consumers’ attitude

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Schlosser, A. E., Shavitt, S., & Kanfer, A. (1999). Survey of internet users’ attitudes toward

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Tan, W., Kwek, C., & Li, Z. (2013). The antecedents of effectiveness interactive advertising in

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on social networks? How gender and age shape receptivity. Journal of Advertising Research,

51(1), 258-275.


Appendix

Survey Items will be measured on a 5-point Likert-type scale to add up the sum of the responses. Introductory Items

• I like Facebook advertising. • I like to look at most advertisements that I am exposed to on Facebook.

Independent Variable: Perception of Facebook Advertising Relevance

• Advertising on Facebook is a good source of current and up-to-date product information. • Advertising on Facebook supplies product information that is relevant to me. • When viewing Facebook ads, I think about how the product might be useful for me. • **Facebook ads do not have anything to do with me or my needs.

Trustworthiness • Facebook advertisements seem trustworthy. • I feel confident using information in a Facebook ad to help me make a purchasing

decision. • I feel security when using advertising on Facebook.

Entertainment Value • Facebook advertising contains a lot of excitement and surprises. • Facebook ads are lots of fun to view. • Facebook advertising usually has great entertainment value to me. • Facebook advertisements seem clever.

Informativeness • Facebook advertising is a valuable source of information about the product. • Facebook advertising informs me of the latest products available on the market. • Facebook ads are a convenient source of product/service information.

Dependent Variable: Attitude towards Advertised Brand Action Tendency

• I often click on Facebook advertisements. • When I view Facebook ads, I think of reasons why I would buy or would not buy the

brand’s product. • Facebook advertising helps me make purchasing decisions from a specific brand. • After viewing Facebook advertisements, I become interested in making a purchase from

the advertised brand. • After viewing Facebook advertisement, I will purchase from the brand being advertised.

Personal Evaluation • I take pleasure in thinking about what I see in Facebook advertisements. • The brands advertised on Facebook reflect who I am.


• The brands advertised on Facebook are consistent with how I see myself. Emotional Feeling

• Advertised brands help me to know which products reflect my unique personality. • After viewing online advertisements, I am more committed to the advertised brand. • After viewing an online advertisement, I develop preference for the brand in the

advertisement. Look at the ad below. Answer the following questions based on your opinion of the ad.

• I am familiar with this brand. (Relevance) • My attitude toward this brand is good. (Emotional Feeling) • The product in the ad is relevant to me. (Relevance) • I am more likely to view cell phone service ads positively when I have preference for the

brand. (Relevance) • It is important to me that I choose the right brand when selecting cell phone services.

(Personal Evaluation) • I feel that each brand of cell phone service is relatively equal in quality. (Personal

Evaluation)


Look at the ad below. Answer the following questions based on your opinion of the ad.

• While experiencing the ad, I feel as if I were taking part in it. (Entertainment Value) • Thoughts and images come to me while experiencing the ad without the slightest effort

on my part. (Relevance) • I can personally relate to aspects of the ad. (Relevance) • I characterize this product as primarily an enjoyable product. (Emotional Feeling) • I get a sense of excitement when I view this ad. (Entertainment Value) • While experiencing the ad, I felt that I “became” her/him for the time being. (Relevance) • My attitude toward this brand is good. (Emotional Feeling) • I am more likely to view credit card ads positively when I have preference for the brand.

(Relevance) • It is important to me that I choose the right brand when selecting credit card companies.

(Personal Evaluation) • I feel that each brand of credit cards is relatively equal in quality. (Personal Evaluation)

**These items require reverse coding.


Tables

Reliability Scale: Relevance

Case Processing Summary

N %

Cases

Valid 81 95.3

Excludeda 4 4.7

Total 85 100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's Alpha

N of Items

.802 11

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

Deleted

Rel1 30.0494 37.823 .533 .778 Rel2 29.8395 36.411 .602 .770 Rel3 30.1975 36.485 .646 .766 Rel5 28.5802 44.922 .050 .822 Rel6 29.9012 41.490 .270 .806 Rel7 29.3086 41.241 .356 .796 Rel8 29.7531 36.688 .642 .766 Rel9 30.1111 38.450 .499 .782 Rel10 30.5432 37.651 .587 .773 Rel11 29.4198 40.797 .374 .795 Rel4REV 29.7037 38.861 .487 .783


Reliability

Notes

Output Created 06-NOV-2013 08:31:02 Comments

Input

Active Dataset DataSet1 Filter <none> Weight <none> Split File <none> N of Rows in Working Data File

85

Scale Statistics

Mean Variance Std. Deviation N of Items

32.7407 46.469 6.81685 11


Matrix Input

Missing Value Handling

Definition of Missing User-defined missing values are treated as missing.

Cases Used Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY /VARIABLES=Trust1 Trust2 Trust3 /SCALE('Trust') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.

Resources Processor Time 00:00:00.00

Elapsed Time 00:00:00.00

[DataSet1] Scale: Trust


N %

Cases

Valid 84 98.8

Excludeda 1 1.2

Total 85 100.0



Cronbach's Alpha

N of Items

.783 3


Scale Mean if Scale Variance Corrected Cronbach's


Item Deleted if Item Deleted Item-Total Correlation

Alpha if Item Deleted

Trust1 4.21 2.725 .589 .749 Trust2 4.70 2.718 .730 .588 Trust3 4.37 3.200 .559 .770

Scale Statistics


6.64 5.847 2.418 3

Reliability

Notes


Input

Data I:\Alex-Abbey-Jay.sav Active Dataset DataSet1 Filter <none> Weight <none> Split File <none> N of Rows in Working Data File

85

Matrix Input




Syntax

RELIABILITY /VARIABLES=EV1 EV2 EV3 EV4 EV5 EV6 /SCALE('Entertainment Value') ALL


/MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



[DataSet1] I:\Alex-Abbey-Jay.sav Scale: Entertainment Value


N %

Cases

Valid 82 96.5

Excludeda 3 3.5

Total 85 100.0



Cronbach's Alpha

N of Items

.895 6






Deleted

EV1 10.93 14.908 .829 .860 EV2 11.05 15.356 .790 .867 EV3 10.94 15.070 .749 .872 EV4 10.78 15.013 .699 .880 EV5 10.35 15.219 .629 .892 EV6 10.22 15.309 .645 .888


Scale Statistics


12.85 21.361 4.622 6

Reliability

Notes


Input


85

Matrix Input




Syntax

RELIABILITY /VARIABLES=Info1 Info2 Info3 /SCALE('Informativeness') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Informativeness


N %


Cases

Valid 83 97.6

Excludeda 2 2.4

Total 85 100.0



Cronbach's Alpha

N of Items

.918 3






Deleted

Info1 5.00 4.610 .790 .918 Info2 4.82 4.272 .860 .861 Info3 4.66 3.934 .860 .863

Scale Statistics


7.24 9.234 3.039 3

Reliability

Notes


Input Data I:\Alex-Abbey-Jay.sav Active Dataset DataSet1 Filter <none>


Weight <none> Split File <none> N of Rows in Working Data File

85

Matrix Input




Syntax

RELIABILITY /VARIABLES=Action1 Action2 Action3 Action4 Action5 /SCALE('Action Tendency') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Action Tendency


N %

Cases

Valid 82 96.5

Excludeda 3 3.5

Total 85 100.0



Cronbach's Alpha

N of Items


.915 5






Deleted

Action1 8.18 14.028 .685 .914 Action2 7.51 12.623 .714 .914 Action3 7.74 12.440 .853 .881 Action4 7.66 12.302 .875 .876 Action5 7.93 13.772 .818 .892

Scale Statistics


9.76 19.940 4.465 5

Reliability Notes


Input


85

Matrix Input




Syntax RELIABILITY


/VARIABLES=PersonEval1 PersonEval2 PersonEval3 PersonEval4 PersonEval5 PersonEval6 PersonEval7 /SCALE('Personal Evaluation') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Personal Evaluation


N %

Cases

Valid 81 95.3

Excludeda 4 4.7

Total 85 100.0



Cronbach's Alpha

N of Items

.561 7






Deleted

PersonEval1 18.35 9.379 .475 .448 PersonEval2 17.64 8.008 .574 .381 PersonEval3 17.80 7.910 .653 .348


PersonEval4 16.10 11.565 .197 .551 PersonEval5 17.60 10.992 .156 .572 PersonEval6 16.36 11.683 .095 .587 PersonEval7 17.48 12.903 -.097 .647

Scale Statistics


20.22 13.125 3.623 7

Reliability

Notes


Input


85

Matrix Input




Syntax

RELIABILITY /VARIABLES=Emo1 Emo2 Emo3 Emo4 Emo5 Emo6 /SCALE('Emotional Feeling') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.




[DataSet1] I:\Alex-Abbey-Jay.sav Scale: Emotional Feeling


N %

Cases

Valid 79 92.9

Excludeda 6 7.1

Total 85 100.0



Cronbach's Alpha

N of Items

.756 6






Deleted

Emo1 13.85 8.977 .603 .689 Emo2 14.10 9.143 .673 .671 Emo3 14.05 9.536 .630 .686 Emo4 12.68 11.809 .169 .802 Emo5 12.85 9.669 .472 .729 Emo6 12.59 10.808 .497 .725

Scale Statistics


16.03 13.717 3.704 6


Reliability

Notes


Input


85

Matrix Input




Syntax

RELIABILITY /VARIABLES=PersonEval1 PersonEval2 PersonEval3 PersonEval4 PersonEval6 PersonEval7REV PersonaEval5REV /SCALE('Personal Evaluation - 7REV 5 REV') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



[DataSet1] I:\Alex-Abbey-Jay.sav


Reliability

Notes


Input


85

Matrix Input




Syntax

RELIABILITY /VARIABLES=PersonEval1 PersonEval2 PersonEval3 PersonEval4 PersonEval6 PersonEval7REV /SCALE('Personal Evaluation - 7REV 5 Remove') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Personal Evaluation - 7REV 5 Remove


N %

Cases Valid 81 95.3


Excludeda 4 4.7

Total 85 100.0



Cronbach's Alpha

N of Items

.666 6






Deleted

PersonEval1 16.2469 9.488 .422 .616 PersonEval2 15.5432 7.976 .551 .560 PersonEval3 15.7037 8.061 .592 .544 PersonEval4 14.0000 10.625 .359 .639 PersonEval6 14.2593 10.244 .314 .651 PersonEval7REV 14.8642 11.094 .156 .700

Scale Statistics


18.1235 12.935 3.59647 6

Reliability

Notes


Input Data I:\Alex-Abbey-Jay.sav Active Dataset DataSet1 Filter <none>


Weight <none> Split File <none> N of Rows in Working Data File

85

Matrix Input




Syntax

RELIABILITY /VARIABLES=PersonEval1 PersonEval2 PersonEval3 PersonEval4 PersonEval6 /SCALE('Personal Evaluation - 1-4 and 6') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Personal Evaluation - 1-4 and 6


N %

Cases

Valid 81 95.3

Excludeda 4 4.7

Total 85 100.0



Cronbach's N of Items


Alpha

.700 5






Deleted

PersonEval1 12.99 7.712 .456 .651 PersonEval2 12.28 6.206 .613 .574 PersonEval3 12.44 6.225 .673 .544 PersonEval4 10.74 9.069 .325 .698 PersonEval6 11.00 8.950 .237 .732

Scale Statistics


14.86 11.094 3.331 5

Reliability

Notes


Input


85

Matrix Input

Missing Value Handling Definition of Missing

User-defined missing values are treated as missing.

Cases Used Statistics are based on all cases with


valid data for all variables in the procedure.

Syntax

RELIABILITY /VARIABLES=PersonEval1 PersonEval2 PersonEval3 PersonEval4 PersonEval6 Action1 Action2 Action3 Action4 Action5 Emo1 Emo2 Emo3 Emo4 Emo5 Emo6 /SCALE('Attitude') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Attitude Case Processing Summary

N %

Cases

Valid 76 89.4

Excludeda 9 10.6

Total 85 100.0



Cronbach's Alpha

N of Items

.914 16




Corrected Item-Total



Correlation Deleted

PersonEval1 38.54 92.572 .696 .906 PersonEval2 37.82 90.419 .663 .907 PersonEval3 37.99 90.386 .705 .905 PersonEval4 36.29 101.062 .316 .916 PersonEval6 36.55 101.931 .192 .921 Action1 38.87 93.449 .655 .907 Action2 38.17 90.224 .675 .907 Action3 38.46 90.145 .793 .903 Action4 38.36 90.259 .786 .903 Action5 38.59 92.618 .765 .904 Emo1 38.24 90.876 .736 .904 Emo2 38.53 92.439 .772 .904 Emo3 38.47 92.786 .790 .904 Emo4 37.04 102.012 .196 .920 Emo5 37.24 96.130 .457 .914 Emo6 36.97 99.093 .469 .913

Scale Statistics


40.41 106.511 10.320 16

Reliability

Notes


Input


85


Matrix Input




Syntax

RELIABILITY /VARIABLES=Per1 Per2 Rel1 Rel2 Rel3 Trust1 Trust2 Trust3 EV1 EV2 EV3 EV4 Info1 Info2 Info3 Rel6 Rel7 EV5 Rel8 Rel9 EV6 Rel10 Rel11 Rel4REV /SCALE('Perception') ALL /MODEL=ALPHA /STATISTICS=SCALE /SUMMARY=TOTAL.



Scale: Perception


N %

Cases

Valid 77 90.6

Excludeda 8 9.4

Total 85 100.0



Cronbach's Alpha

N of Items


.942 24






Deleted

Per1 56.9740 244.184 .636 .939 Per2 57.3117 243.270 .683 .939 Rel1 56.5195 238.437 .716 .938 Rel2 56.2987 239.975 .634 .939 Rel3 56.6883 237.823 .749 .938 Trust1 56.7792 247.885 .473 .941 Trust2 57.2597 243.537 .691 .939 Trust3 56.9091 246.689 .606 .940 EV1 57.2857 242.549 .778 .938 EV2 57.4026 244.375 .734 .938 EV3 57.2987 244.002 .683 .939 EV4 57.1688 241.326 .739 .938 Info1 56.9740 238.552 .783 .937 Info2 56.7662 239.260 .733 .938 Info3 56.6494 236.968 .743 .938 Rel6 56.4156 256.036 .223 .945 Rel7 55.7792 254.490 .310 .943 EV5 56.7143 241.891 .675 .939 Rel8 56.2078 241.588 .644 .939 Rel9 56.5584 246.250 .501 .941 EV6 56.5195 244.674 .604 .940 Rel10 57.0000 241.342 .663 .939 Rel11 55.8571 251.256 .416 .942 Rel4REV 56.1429 248.308 .457 .942


Scale Statistics


59.1948 264.948 16.27724 24

Statistics

Gender Age

N Valid 84 77

Missing 1 8 Mean 1.76 21.64 Mode 2 19 Std. Deviation .428 7.664 Minimum 1 18 Maximum 2 66

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

AttitudeTOTAL 76 1.34 5.00 2.5165 .65013 PerceptionTOTAL 77 1.18 5.00 2.3518 .69773 Valid N (listwise) 73

Test of Covariation Hypothesis

Descriptive Statistics

Mean Std. Deviation N

AttitudeTOTAL 2.5165 .65013 76 PerceptionTOTAL 2.3518 .69773 77

AttitudeTOTAL


PerceptionTOTAL

Pearson Correlation .858**

Sig. (2-tailed) – p-value .000 Sum of Squares and Cross-products

28.315

Covariance .393

N 73

**. Correlation is significant at the 0.01 level (2-tailed).

Test of Difference Hypothesis Statistics Perception TOTAL

N Valid 77

Missing 8 Median 2.3242

Perception2.32LO

Frequency Percent Valid Percent Cumulative Percent

Valid 1.00 – Negative Perception

39 45.9 50.6 50.6

2.00 – Positive 38 44.7 49.4 100.0


Perception

Total 77 90.6 100.0 Missing System 8 9.4 Total 85 100.0

One-way ANOVA

Descriptives AttitudeTOTAL

N Mean Std. Deviatio

n

Std. Error

95% Confidence Interval for

Mean

Minimum

Maximum

Between- Compone

nt Variance

Lower

Bound

Upper Boun

d

1.00 – Negative Perception

38

2.1398

.44046 .0714

5 1.995

0 2.284

5 1.34 3.12

2.00 – Positive Perception

35

2.9143

.61616 .1041

5 2.702

6 3.125

9 2.11 5.00

Total 73

2.5111

.65633 .0768

2 2.358

0 2.664

2 1.34 5.00

Model

Fixed Effects

.53189

.06225

2.3870

2.6352

Random Effects

.3875

7

-2.413

4

7.4357

.29218


ANOVA AttitudeTOTAL

Sum of Squares df Mean Square F Sig.

Between Groups 10.929 1 10.929 38.633 .000 Within Groups 20.086 71 .283 Total 31.016 72

Means Plot


Gender

Frequency Percent Valid Percent Cumulative Percent

Valid

Male 20 23.5 23.8 23.8

Female 64 75.3 76.2 100.0

Total 84 98.8 100.0 Missing System 1 1.2 Total 85 100.0

Statistics

Age


N Valid 77

Missing 8 Mean 21.64 Std. Deviation 7.664 Minimum 18 Maximum 66

Survey Link https://ugeorgia.qualtrics.com/SE/?SID=SV_3ZP25WnbjvsFV5P

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