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CULTURAL CUES EMBEDDED WITHIN HASHTAGS: EFFECTS ON IDENTIFICATION,
AND ADVERTISING OUTCOMES
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THESIS
Presented in partial Fulfillment of the Requirements for the Degree Master of Arts
in the Graduate School of The Ohio State University
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By
Isabella B. Harris, B.A.
Graduate Program in Communication
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The Ohio State University
2014
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Thesis Committee:
Professor Osei Appiah, Advisor
Professor J. Roselyn Lee
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Copyright by
Isabella B. Harris
2014
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Abstract
This study examines whether cultural cues embedded within hashtag messages will
influence White viewers’ responses to advertising outcomes, using Social Identity Theory
(Tajfel & Turner, 1979) as a guidance. Cultural cues embedded within hashtag messages
were digitally manipulated while all other visual features of the advertisement maintained
the same. Each participant views one of the three versions (White mainstream hashtag
message, Black, no hashtag message) of the advertisement. The results from this study
indicated that cultural cues embedded within hashtag messages have the ability to
significantly impact how reviewers respond to advertising media. Hashtag messages that
were consistent with the viewer’s perceptions were found to lead to more positive
advertising outcomes. The hashtag messages presented not only influenced how viewers
perceived the advertisement, but actually led to significant different ratings of the
advertisement content.
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Acknowledgements
I want to take the time to thank my two committee members, Dr. Appiah and Dr. Lee. It is
very hard to adequately thank you both for everything I have learned from you during my
graduate studies at The Ohio State University.
Dr. Appiah, thank you so much for leading me this far. My time at graduate school
has not been easy, having to balance my studies, work, and providing for my growing
family. I hardly had anytime to be on campus, but thank you so much for always taking
your extra time to help me to get through everything. Thank you so much for all the
constructive feedback you have provided for me. This thesis would not be possible
without you.
Dr. Lee, thank you so much for always being there for me ever since we have had
our first conversation. I am very grateful for all the help you have given me. This road
would be much more difficult if not for the presence of your encouraging and kind words.
Thank you.
Thank you both so much. I appreciate everything.
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Vita
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2009…………………………………..Undergraduate Research Assistant, School of
Communication, The Ohio State University
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2010…………………………………..B.A. Public Affairs Journalism, The Ohio
State University
2013…………………………………..Graduate Teaching Associate, School of
Communication, The Ohio State University
Fields of Study
Major Field: Communication
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TABLE OF CONTENTS
Page
Abstract…………………………………………………………………………………ii
Acknowledgements…………………………………………………………………….iii
Vita……………………………………………………………………………………..iv
List of Tables………………………………………………………………………….vii
List of Figures………………………………………………………………………..viii
Chapters:
1.
Introduction……………………………………………………………………1
2.
Literature Review……………………………………..……………………….4
Twitter and Hashtag……………………….……..………….….………4
Cultural Cues and Cultural Embeddedness in Advertising……………..7
Social Identity Theory…………………………………………………..9
Distinctiveness Theory…………………………………….……..……11
Hypotheses……….….………….….…..…….….…………………….13
3.
Method……………..…………………………………………………………15
Design…………………………………………………………………15
Procedure………………………..…………………………………….15
Stimulus Materials…………………………………………………….17
Subjects………………………………………………………………..22
Measures………………………………………………………………22
Other Measures….…………………………………………………….24
Manipulation Check.…………………………………………………..25
Cue Recall
Demographic Items……………………………………………………25
4.
Results………………………………………….……………..………………26
Manipulation Check………………….…..……………………………26
Main Analyses………….…………….…..……………………………26
Additional Findings……………………………………………………31
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Conclusion……………………………………….….….…………………….32
Summary of Findings……….………………..……………………….32
Limitations and Future Directions….……………….………………..35
References……..………………………………………………………………………38
Appendix A: Study Questionnaire Instructions and Items…..….….….………………42
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LIST OF TABLES
Table
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4.1
Means and SDs for Study Dependent Variables as a Function
of Cultural Cues and Ethnic Identity..…….…..……………………………30
4.2
Means and SDs for Study Dependent Variables as a Function
of Cultural Cues…………………………………………………………….30
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LIST OF FIGURES
Figure
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3.1
Study Stimulus Advertisement — Ambiguous Character with:
A #AmericanPride B #BlackPride C No Hashtag….…………….……….…19
4.1
Effects of Cultural Cues on Advertising Outcomes.…….…………………..31
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CHAPTER 1
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INTRODUCTION
The ever-updating technology is not only transforming the way people communicate with
each other, it also changes the strategies for corporations and government to
communicate with people. Not only start-up businesses try to build relationships with
consumers through social networking sites; in fact, almost all top 10 Fortune 500
companies have their own social media verified account (e.g. Twitter). Government
officials and organizations also constantly update information on their social media
accounts. People can now easily get instant new information through one click on the go.
This has completely changed the information technology landscape. On the one hand,
Twitter has become a simple way to narrow the knowledge distance between the general
public and the officials because of its instant and easy access. On the other, Twitter has
also become an important form to promote products and brand, and there are more and
more advertisements featuring hashtag messages with the intention to attract more
consumers.
One thing about the advertising media different from other media is that due to its
short nature, advertising media usually does not allow for complex interaction between
the viewers and the advertisement (e.g. media characters, theme of the ad) where
potential similarities and differences can be revealed. Thus viewers must rely on what
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little visual or textual cues are present in an advertisement (e.g. print) to establish
perceptions about the advertisement, the brand, and the product. Consequently, cultural
features within media advertisements that can provide background information about the
advertisement are likely to play a significant role in similarity perceptions and judgments
about the the brand and the product. According to Kelman’s (1958, 1961, 1974) typology
of social influence, the perceived similarity with the message source can shape one’s
attitude that is similar to those of the source. Thus when the cultural cues that are similar
to the viewers are reflected through hashtag messages, it should subsequently influence
viewers’ perceived similarity with the source and responses to advertisements (e.g. brand
attitudes, purchase intentions). However, studies have yet to investigate the role of
background cultural cues embedded within hashtag messages in identification processes
and the effects when cultural cues incorporated into hashtag messages for an
advertisement. While more and more hashtag messages are being used in a variety of
advertisements, it is important to understand the role of cultural cues within hashtag
messages and subsequent advertising responses. It is also vital for practitioners to
understand how viewers are likely to respond to advertising messages. Through analyzing
this important issue, this thesis tend to explore how the advertising outcomes may be
impacted when cultural cues are represented through hashtag messages in an
advertisement.
This thesis consists of one study in which Twitter usage is examined and cultural
cues (i.e. hashtag messages) are experimentally manipulated. The goal of this
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investigation is to examine how viewers use hashtag messages to judge the
advertisement, how viewers identify the influence on advertisement evaluations, and how
identification may interact with the cultural cues to influence the advertising outcomes. In
the first part of the study, participants were asked to answer Twitter and hashtags related
questions. In the second part of the study, racial cultural cues (embedded within hashtag
messages) were used in print advertisements to determine whether this can impact
advertising outcomes.
The following sections lay out the theoretical foundations for this investigation.
First, because the growing popularity of Twitter is the basis for the subsequent
examination, Twitter-related concepts and descriptions will be reviewed. Second, because
hashtag messages will be manipulated as a type of cultural cues, the phenomena of
cultural embeddedness in advertising will be reviewed. Social identity theory (SIT; Tajfel
& Turner, 1979) will be reviewed and examined on why it is applicable in this situation.
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CHAPTER 2
LITERATURE REVIEW
Twitter and Hashtags
Twitter is a special form of social media, which could be summarized as “webbased services that allow individuals to (1) construct a public or semi-public profile
within a bounded system, (2) articulate a list of other users with whom they share a
connection, and (3) view and traverse their list of connections and those made by others
within the system (Boyd & Ellison, 2007).” The social media revolution may be
described as a time when “we get as much information from each other as we do from
media” (Dubose, 2011).
The idea of Twitter was first built on sending text messages to and from a small
group of recipients. Since it was heavily relied on mobile texting and the worldwide
standard length of SMS was (is) 160 characters, creators of Twitter decided to have a
limit of 140 characters for each tweet so that people can condense their ideas and really
get at the essential points that they are trying to make. Through just 140 characters,
thoughts are being shared, arguments are being presented and connections are being
created across the globe. With Twitter, communication can easily be one-to-one, one-tomany, and many-to-many. Twitter not only serves as a source, it also serves as a forum to
express feelings and ideas fast and freely. It allows everyone to search for related
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messages and have conversations about it. Twitter also gives people the ability to
communicate quickly and effectively, revolutionizing the manner in which people gather
information and topics that are of interest to them, so businesses and organizations are
implementing social media strategies (e.g. hashtag message in an advertisement or TV
commercials) as part of their promotional effort and taking advantage of its efficiency to
reach more audiences in a much faster speed. Twitter has been described as “the SMS of
the Internet,” revealing the fact that Twitter has been one of the most visited websites on
the Internet with fast message exchange capability.
“Tweets,” as the messages are called, are a constant stream of information about
the lives of each user or the ideals and perspectives of each business or organization.
Each tweet can be about anything, from service announcement, to self-promotion, to even
just asking the followers how they are doing in their everyday life. Tweets are accessible
from a device with Internet capabilities. Users tweet messages to members of their social
group and can search for tweets by entering specific keywords or phrases (Dubose, 2011).
It is also worth noting that while registered users can post and read tweets through
Twitter.com, SMS, and/or a wide range of apps from different mobile devices,
unregistered users can also search profiles and read tweets that are of their interests, as
long as the registered users’ profile are not set to be private. Usually companies’ verified
Twitter accounts will always be open to the public regardless of the status of the user
(whether or not registered to run a Twitter account) to get the maximized exposure to all
possible audiences. Hashtag can be added to each tweet to help individuals interested in a
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topic find and participate in the discussion. One hashtag message (e.g. #BlackHistory) or
a series of hashtag messages (e.g. #BlackHistory #MLK) can also be considered as a
tweet if Twitter users want it/them to be.
A hashtag is simply anything prefixed with the symbol #. One can search for the
hashtag message and get all the tweets that contain it. The popularity of hashtag grew
with the popularity of Twitter, and tweeting a message with hashtag(s) has become the
writing practice of Twitter posts. According to its website, Twitter began to hyperlink all
hashtags in 2009 to search results mentioning the hashtags or standard spelling of the
words. Twitter also introduced the “trending topic” function on the front page with a
search bar and a side bar, the more people talk about that hashtag message, the more
frequent such hashtag message will appear under trending topic. With this newly
launched feature, Twitter has become something unexpectedly important—a discovery
engine for finding out what is happening right now (Stone, 2009).
When it comes to the Twitter usage and popularity, according to the research
conducted by Edison Research and Arbitron in 2012, 90% of population have heard of
Twitter (compatible with Facebook for 93%). According to Pew Research Internet Project
of 2012, more than one quarter of online Blacks (28%) use Twitter, roughly twice their
share of the population in general. It is very clear that Twitter usage varies among
different racial groups. It shows that the popularity of Twitter literally has no race/
ethnicity boundaries, as well as the fact that social media users do differ in race/ethnicity
group on whether they use Twitter or how much they use Twitter. This difference also
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provides explanations of why businesses may use cultural cues embedded within hashtag
messages to tailor or target at audiences from different racial groups.
Cultural Cues and Cultural Embeddedness in Advertising
Due to the increased popularity of Twitter, more and more brands start to utilize its
byproduct—hashtag messages in advertisements intending to increase brand and product
visibility and reputation. It thus raises the question of how viewers would respond to
advertisements featuring hashtag messages with cultural cues embedded, especially the
sole impact of hashtag messages when other information in the advertisement stays the
same.
Early studies have suggested that the model’s race in an advertisement was enough
to provoke positive target consumer effects (Barban & Cundiff, 1964; Barban, 1969), and
recent research suggests that tailored cultural cues may be necessary, particularly among
the ethnic minorities (Appiah, 2003; Appiah & Liu, 2009). Cultural cues refer to the
values, symbols, ethics, rituals, traditions, material objects, and services produced or
valued by either Black or White members of society (Appiah, 2001b). Advertisements
rich in cultural cues may be considered culturally embedded, which is conceptualized as
the degree to which cultural cues are present in an advertisement (Appiah, 2001b).
Past research also suggested that culturally embedded advertisements are likely to
be more effective in reaching consumers who identify with the presented culture. For
example, in Whittler’s study (1989), he found that Whites, especially high-prejudiced
Whites, perceived themselves as less similar to Black than to White actors, and more
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difficult to identify with the Black than the White actor.
Research (e.g. Appiah, 2001a) also suggested that studies that examined viewer
responses to race in advertising have a tendency of experimentally manipulating the race
of ad models, but not the cultural context in which these models appeared. Even though
Twitter and hashtags are growing popularity each day, it is still much less known
regrading how White viewers respond to cultural cues embedded within hashtag
messages, without other obvious cues (e.g. race of the advertising character). It is
important to understand White viewers’ response to such advertisements for at least two
reasons. On the one hand, according to the U.S. Census Bureau (2011) report, the growth
rate of the United States population was 9.7% from 2000 to 2010, while the number of
people who reported their race as White alone grew by only 1% during this time period. It
is clear that racial minority groups are growing at a faster rate than Whites. This fact also
clearly indicates an increasing presence of minority groups (e.g. Hispanics, Asian
American) in U.S. life and culture. Moreover, with the fact that there are more and more
positive portrayals of minorities in the media (including advertising media), it also
becomes crucial to understand White responses to race in advertising, particularly when
something as small as a hashtag message, as their attitudes may shift over time. This
study will fill the gap in the literature and addresses little findings from past research of
White viewer responses to race cues by examining the cultural cues embedded within
hashtag messages in advertising. SIT argues that individuals have a clear sense of which
group they belong, which will in turn help provide a definition of the self (Abrams &
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Hogg, 1988). Thus it may indicate that the hashtag message that are related to specific
ethnic group (i.e. African American) may be more likely to lead White viewers to
perceive dissimilarity and less favorable attitudes toward the advertisement and their
subsequent advertising responses. But a clearer review is needed to lead this discussion.
Social Identity Theory
Social identity theory was originally developed to capture aspects of intergroup
categorization and group dynamics associated with large-scale social identities such as
races, nations, and so forth (Reed, 2002). Tajfel and Turner argued that the motivating
principle underlying competitive intergroup behavior was a desire for a positive and
secure self-concept (Hornsey, 2008). SIT proposes that people are motivated to achieve
and maintain that positive concepts of themselves (Tajfel & Turner, 1979), and this
positive identity derives largely from favorable comparisons that can be made between
the ingroup and relevant outgroups (Brown, 2000). If we accept the idea that people are
motivated to have a positive self-concept, then it is naturally to believe that people are
motivated to think that the groups they are in are good groups. Thus SIT also argues that
the ingroup and outgroup comparisons are not necessarily based in reality, but may be
subjectively constructed through their sense of social identity (Hogg et al., 1995).
SIT has recently been used by media scholars to explore how media portrayals of
ingroup or outgroup members function to influence viewer perceptions (Mastro, 2003;
Fujioka, 2005), to understand the media’s role in the development and enhancement of
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social identities (Harwood, 1999), and to see their potentials to impact attitudes and
behavior (Coover, 2001; Mastro, 2003). In media contexts, dozens of research have been
conducted to hypothesize that the exposure to ingroup or outgroup members will
affect the social identity of viewers depending on the portrayal of the group. For example,
Harwood (1999) has found that respondents seek to view individuals with similar
characteristics to themselves. Younger adults are more likely to seek out media
experience that features younger characters rather than older adults. Moreover, social
identity reinforcement is sought by more highly identified viewers, but not by those less
strongly identified (Harwood, 1999).
However, there has been some contradictory findings in research indicating that
ingroup members might respond no difference to media content featuring ingroup or
outgroup members. For example, in Appiah (2001b)’s research, it has shown that White
adolescents’ responded no differently to advertisements featuring either White or Black
models. But it is also important to notice that previous studies may did not elicit the sense
of competition for the ingroup members (e.g. White) with outgroup members (e.g.
Black), which was an assumption of SIT was based on. Sports, for example, is one of the
events that could cause the competitive sense for White viewers when seeing Black in
media content because unlike other domains (e.g. media, health, education), Black
actually outshines White in sports most of the time. Due to the fundamental desire to
maintain a positive social identity, when seeing a Black athlete in the media content (e.g.
advertisement), White viewers should subsequently favor the ingroup member (i.e.
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White) rather than the outgroup member (i.e. Black).
Cultural cues embedded within the advertisement may be a direct impact to
viewer’s responses, because the principles of SIT stipulate that the ingroup identity of
race will be amplified for White viewers if they are exposed to an advertisement with
predominantly Black cultural cues that can elicit the sense of competition. In such case,
their ingroup membership has become salient, making them even harder to identify with
the advertisement and the rating of the advertisement will subsequently decrease.
Distinctiveness Theory
Distinctiveness theory suggests that a person’s own distinctive traits will be more
salient to him or her than more prevalent traits possessed by other people in his or her
environment (McGuire, 1984; McGuire, McGuire, Child & Fujioka, 1978; Appiah,
2001b). Distinctiveness theory also suggests that altering a person’s social environment
such that different physical characteristics become distinctive will lead to a change in a
person’s self-concept (McGuire et al., 1978; Appiah, 2001b). For example, a White
woman entering a room full of Black women should suddenly become mindfulness of her
whiteness. However, when entering a room full of White man, she would be more
conscious of her gender rather than her ethnicity.
Distinctiveness theory was developed by McGuire in the 1970s, however, it wasn’t
applied to advertising until the 1990s. In one study, Deshpande and Stayman (1994)
conducted an empirical study to test this theory within an advertising context. They found
that members of minority groups were more likely than majority groups to have their
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ethnicity salient. It was worth noting that White can be either a minority group or
majority depending on which city they lived in this study. They also found that members
of minority groups would find an ad spokesperson from their own ethnic group to be
more trustworthy and this would lead to more positive attitudes toward the brand being
advertised. This study laid a good foundation in applying distinctiveness theory to
advertising context. It may follow that for people with strong ethnic identities, more racespecific cultural cues used in an advertisement will lead to more positive attitude toward
the advertisement and the subsequent advertising responses. Ethnic identity is defined as
a person’s knowledge of his or her membership in social group and the value and
emotional significant attached to that membership (Phinney, 1992; Appiah, 2004).
Donthu and Cherian (1992) argued that the stronger the ethnic identity, the more loyal
ethnic groups are to their traditional values and the more likely they are to exhibit these
values (Appiah, 2004).
In exploring how viewer’s cultural identification may impact evaluation of
advertisements, previous studies have focused on the ethnic minority groups (e.g. Black,
Hispanic) by utilizing distinctiveness theory. One reason is that White ethnic identity is
commonly portrayed as a default racial category, an invisible yet privileged identity
formed by centuries of oppression of nonwhite groups (McDermott & Samson, 2005).
However, the fact that the demographic changes in the racial makeup of the U.S.
population and increasing numbers of Asian and Hispanics resulting in a corresponding
shrinking of the relative size of the white population, indicates that the existence of
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Whites as a racial category rather than as a default identity (McDermott & Samson,
2005). Ethnic identity for Whites in advertising practice or studies has been largely
ignored because it has been treated as base group to which others are compared without
having a real racial identity. Past research have shown that minority group members (e.g.,
Blacks) consistently place higher importance on their racial and ethnic identity than do
whites (Phinney, 1992; Appiah, 2001b). However, With the shrinking size of the white
population as well as the increased presence of nonwhites in prominent positions
(McDermott & Samson, 2005), it has rendered “White” more visible rather than as a
default category and “White” may have become a distinctive trait for them. Based on the
above discussion, the following hypothesis are proposed:
H1a: White viewers will report greater identification with advertising characters when
White mainstream hashtag message is present in the advertisement, compared to Black
cultural cues.
H1b: H1a may be qualified by an ethnic identity interaction such that those White
viewers with high ethnic identity will have stronger identification with advertising
characters when White mainstream hashtag message is present in the advertisement,
compared to Black cultural cues.
H2a: White viewers will more likely believe ads are intended for them when White
mainstream hashtag message is present in the advertisement, compared to Black cultural
cues.
H2b: H2a may be qualified by an ethnic identity interaction such that those White
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viewers with high ethnic identity will have stronger beliefs that ads are intended for them
when White mainstream hashtag message is present in the advertisement, compared to
Black cultural cues.
H3a: White viewers will report more positive attitudes toward the advertisement when
White mainstream hashtag message is present in the advertisement, compared to Black
cultural cues.
H3b: H3a may be qualified by an ethnic identity interaction such that those White
viewers with high ethnic identity will respond more favorably to the advertisement when
White mainstream hashtag message is present in the advertisement, compared to Black
cultural cues.
H4a: White viewers will report more positive attitudes toward the product when White
mainstream hashtag message is present in the advertisement, compared to Black cultural
cues.
H4b: H4a may be qualified by an ethnic identity interaction such that those White
viewers with high ethnic identity will respond more favorably to the product when White
mainstream hashtag message is present in the advertisement, compared to Black cultural
cues.
H5a: White viewers will report more positive attitudes toward the brand when White
mainstream hashtag message is present in the advertisement, compared to Black cultural
cues.
H5b: H5a may be qualified by an ethnic identity interaction such that those White
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viewers with high ethnic identity will respond more favorably to the brand when White
mainstream hashtag message is present in the advertisement, compared to Black cultural
cues.
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CHAPTER 3
METHOD
Design
Each White subject was randomly exposed to one of the three different
advertisement conditions, with White mainstream hashtag message, Black cultural cue
hashtag message, and no hashtag message. The advertisement featured a fictitious sports
drink product which was assigned an unfamiliar brand name to prevent existing brand
attitudes from influencing the study results. Participants were randomly exposed to one of
the three advertisements and asked to respond to a number of items about the
advertisement. Demographic items were recorded at the beginning of the questionnaire
followed by questions regarding Twitter and hashtags.
Procedure
Participants in this study were recruited from undergraduate communication
courses and Communication Research Experience Program (CREP), and received extra
course credit for participation. At the beginning of the questionnaire, participants were
first instructed to sign a consent form if they agreed to participate the study. In the
consent form, information regarding the voluntary nature of the study was provided, and
participants were promised that all study data was both confidential and anonymous. If
participants had used Twitter before, they were instructed to answer questions regarding
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Twitter; if not, they would automatically skip this section and answer some items
regarding hashtags. Following the hashtag questions were the print advertisements.
Participants would respond to the rest of the questionnaire based on the viewing of the
advertisement. Study participation took place in a location where participants had online
access to the questionnaire. The questionnaire was created using Qualtrics survey
software.
Stimulus Materials
Participants viewed one of three versions of the sports drink advertisement in
which the character race was ambiguous and hashtag messages were manipulated. It was
desirable to utilize a product relevant to college students, and not associated with a
specific racial group. Everything in the advertisement is the same except for the cultural
cues embedded within the hashtag messages. Since one purpose of the investigation is to
examine the hashtag effects, besides the White mainstream cues (#AmericanPride) and
Black cultural cues (#BlackPride), there is an additional condition being no hashtag
message embedded at all.
Pride Sports Drink Ads
The Pride sports drink advertisement features an racially ambiguous character
running towards the Pride drink, which stands in the center of the print advertisement.
Participants can only see the back of the racially ambiguous character in the
advertisement. One of the reasons for using racially ambiguous character are because the
primary interest of the study is to evaluate the sole effects of cultural cues embedded in
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hashtag messages. Another reason is because relatively little is known regarding how
viewers would respond to advertisements featuring racially ambiguous character, and if
cultural cues embedded within hashtag messages will guide perceptions of ambiguous
models.
The texts on top of the advertisement read, “Take down a Pride Drink in the
moments leading up to the game,” and “Introducing the complete sports drink.” There are
also three additional lines (one on the left, two on the right), indicating the benefits of this
drink. Each line reads as the following, “Energy—Fuel for everyday athletes,”
“Hydration—help replace what’s lost in sweat,” and “Recover—protein to help replace
muscle.”
The above descriptions are the same for each ad condition. The only difference is
that on the bottom right, for White mainstream cue condition, it will show the text of
“#AmericanPride” and the symbol for Twitter (the bird with white fleece); for Black cue
condition, it will show the text of “#BlackPride” and the same symbol for Twitter; and for
no hashtag condition, there will be nothing on the bottom right corner. See Figure 3.1 for
Study advertisements.
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continued
A
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Figure 3.1
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Study Stimulus Advertisement — Ambiguous Character with:
A #AmericanPride B #BlackPride C No Hashtag
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Figure 3.1: continued
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B
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Figure 3.1: continued
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C
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Subjects
White (N = 177) undergraduate students from a large Midwestern university took
part in this study on a voluntary and confidential basis. Because all hypotheses were
premised upon the effects for White viewers, responses from other ethnic and racial
groups were omitted from analyses. Participants selecting more than one racial
background (e.g. White and Asian) were also removed from final analyses to prevent
differences in racial makeup from influencing responses. The sample was 64% female (N
= 114), and 36% male (N = 63). Mean age was about 21 years, with about 70% of
students coming from junior or senior class ranks.
Measures
Ethnic Identity. The revised version of Multigroup Ethnic Identity Measure
(Phinney, 1992) will be used to measure to what extent participants identify with their
ethnicity. This revised measure, with five different questions, comprises of two important
factors in analyzing ethnic identification: ethnic identity search (a developmental and
cognitive component) and affirmation, belonging, and commitment (an affective
component), (Roberts et al., 1999). The five items were, “I have a lot of pride in my
ethnic group,” “I have a strong attachment towards my own ethnic group,” “I have a clear
sense of my ethnic background and what it means for me,” “I am happy that I am a
member of the group I belong to,” and “I have a strong sense of belonging to my own
ethnic group.” Each item was measured using a 7-point Likert scale ranging from
strongly disagree (1) to strongly agree (7). This scale reached a reliability of alpha = .881.
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The median ethnic identity score for White viewers was 24. High and low ethnic
identifiers scored either above or below the median for their racial group.
Attitude toward ad (Aad). Subjects’ attitude toward the ad was measured using a 7point Likert scale, adapted from Run and Gray (2005). There were nine statements
including, “The ad is good,” “The ad is interesting,” “The ad is informative,” The ad is
appropriate,” “The ad is easy to understand,” “The ad is objective,” “The ad is
distinctive,” “The ad is inappropriate (will be reverse scored),” and “The ad is offensive
(will be reverse scored).” A single Aad index was created by computing the mean sore of
the nine items. This scale has been found reliable and in this study it reached the
reliability of alpha = .809.
Attitude toward product (Apr). Adapting from Petty et al. (1983)’s study,
participants will be asked to rate their overall impression of the product on four 7-point
semantic differential scales (Bad—Good, Unsatisfactory—Satisfactory, Unfavorable—
Favorable, and Dislike-Like). A single Apr index was created by computing the mean
sore of the four items. This scale reached a reliability of alpha = .970 in this study.
Attitude toward brand (Abr). Attitude toward the brand was measured by having
participants their agreement with the following eight items: 1) This brand’s product
claims are believable, 2) This brand has a name you can trust, 3) This brand has the
ability to deliver what it promises, 4) Knowing what I’m going to get from this brand
saves me time shopping around, 5) This brand gives me what I want, which saves me
time and effort trying to do better, 6) I need lots more information about this brand before
23
I’d buy it (will be reverse coded), 7) I would never buy this brand (will be reverse coded),
and 8) I would seriously consider purchasing this brand. All eight items will be measured
on a 7-point Likert scale (1 = Strongly Disagree, 7 = Strongly Agree). This measure was
adapted from Brand Constructs Measurement Model (Erdem, Swait & Valenzuela, 2006).
A single Abr index was created by computing the mean sore of the eight items. This scale
has been found reliable and in this study it reached the reliability of alpha = .856.
Other Measures
The last two dependent variables were ads intended for me and identification with
ad character, both adapted from Aaker et al. (1996)’s study. Participants were asked to
indicate whether they thought each advertisement was intended for them on a seven-point
Likert scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). Participants were
also asked to indicate how strongly they identified with the character in each
advertisement on a seven-point Likert scale ranging from 1 (Not at all) to 7 (Very much).
Purchase intentions has been directly linked to attitude toward product in the past,
so it was also used as a exploratory dependent variable to see whether the cultural cues
embedded within hashtag messages will have any influence on this behavioral intention.
Adapted from Petty et al. (1983)’s study, participants will be asked to rate, on a four-point
scale, how likely it would be that they would purchase the Pride drink “the next time you
needed a product of this nature.” The descriptions for each scale value were: 1= “I
definitely would not buy it,” 2= “I might or might not buy it,” 3= “I would probably buy
it,” and 4= “I would definitely buy it.”
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Manipulation Check
Cue recall. Participants were asked to recall the hashtag message in the
advertisement they saw. This open-ended item was used to determine whether
participants noticed and remembered the cultural cue present in the advertisement.
Participants receive a score of either 1 or 0, indicating whether the cultural cue was
correctly identified or not.
Demographic Items
Before answering questions regarding Twitter and hashtag and viewing the
advertisement, participants were asked a number of demographic items including their
major, class standing, age, gender, and race. Respondents were instructed to select as
many racial groups as apply to them.
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CHAPTER 4
RESULTS
Manipulation Check
It was first derivable to determine whether participants noticed and could recall
the cultural cue manipulated in this study. Although it is possible that advertising stimuli
may influence advertising outcomes even if they were not specifically remembered, the
hashtag effects are less likely to be observed if participants did not pay attention to the
cues at all. Results indicate that about 79% of participants could accurately recall the
hashtag message from the advertisement, indicating the manipulation of context cues was
observed and processed by participants. No significant differences were found in cue
recall based on the type of hashtag messages present in the advertisements.
Main Analyses
The hypotheses presented in the study predicted a main effect of cultural cues on
the dependent measures, with an ethnic identity interaction. To address the hypotheses, a
two-way analysis of variance (ANOVA) with cultural cues (White, Black, no hashtag)
and ethnic identity (high, low) as between-factors was run for each dependent variable.
Influence of Hashtag Messages on Identification with the Character
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on identification with the
26
advertisement character. Means and standard deviations for identification with the
character as a function of the two factors can be found in Table 4.1. The ANOVA
indicated a marginally significant main effect for cultural cues embedded in hashtag
messages on character identification, F (2, 161) = 2.464, p = .088, ηρ² = .030. Follow up
pairwise comparison indicated that viewers who were exposed to the ad with White
cultural cues (M = 3.39, SD = 1.56) reported greater identification with the ad character
than viewers exposed to the ad with Black cultural cues (M = 2.81, SD = 1.71, p = .05),
supporting H1a. However, the interaction between cultural cues embedded in hashtag
messages and ethnic identity was not significant, F (2,161) = .346, p = .708, ηρ² = .004.
Thus H1b was not supported.
Influence of Hashtag Messages on Perceived Intended Audience
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on how much White viewers perceive
the advertisement was intended for people like them. Means and standard deviations for
perceived intended audience as a function of the two factors can be found in Table 4.1.
The ANOVA indicated a significant main effect for cultural cues embedded in hashtag
messages on perceived intended audience, F (2, 161) = 12.873, p < .005, ηρ² = .138.
Follow up pairwise comparison indicated that viewers who were exposed to the ad with
White cultural cues (M = 4.11, SD = 1.73) perceived themselves to be the intended
audience significantly more than viewers who viewed ads with Black cultural cues (M =
2.70, SD = 1.64, p < .005), supporting H2a. The ANOVA model also showed a significant
27
main effect for ethnic identity on perceived intended audience, F (1, 161) = 5.667, p = .
018, ηρ² = .034, however it was not the focus on the study. The interaction between
cultural cues embedded in hashtag messages and ethnic identity was not significant, F
(2,161) = .133, p = .875, ηρ² = .002. Thus H2b was not supported.
Influence of Hashtag Messages on Attitude toward the Advertisement (Aad)
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on Aad. Means and standard
deviations for attitude toward the advertisement as a function of the two factors can be
found in Table 4.1. The ANOVA indicated a significant main effect for cultural cues
embedded in hashtag messages on attitude toward the advertisement, F (2, 161) = 5.480,
p = .005, ηρ² = .064. Follow up pairwise comparison indicated that participants who
viewed ads with White cultural cues (M = 4.36, SD = .90) reported significantly higher
attitudes toward the ad compared to subjects who viewed ads with Black cultural cues (M
= 3.89, SD = 1.09, p = .012), supporting H3a. However, the interaction between cultural
cues embedded in hashtag messages and ethnic identity was not significant, F (2,161) = .
670, p = .513, ηρ² = .008. Thus H3b was not supported.
Influence of Hashtag Messages on Attitude toward the Product (Apr)
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on Apr. Means and standard deviations
for attitude toward the product as a function of the two factors can be found in Table 4.1.
The ANOVA indicated a significant main effect for cultural cues embedded in hashtag
28
messages on attitude toward the product, F (2, 161) = 3.635, p = .029, ηρ² = .043. Follow
up pairwise comparison indicated that participants who viewed the ad with White cultural
cues (M = 3.68, SD = 1.47) reported significantly higher attitudes toward the product
compared to participants who viewed ads with Black cultural cues (M = 3.03, SD = 1.48,
p = .022), supporting H4a. However, the interaction between cultural cues embedded in
hashtag messages and ethnic identity was not significant, F (2,161) = .309, p = .734, ηρ² =
.004. Thus H4b was not supported.
Influence of Hashtag Messages on Attitude toward the Brand (Abr)
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on Abr. Means and standard deviations
for attitude toward the brand as a function of the two factors can be found in Table 4.1.
The ANOVA indicated a significant main effect for cultural cues embedded in hashtag
messages on attitude toward the brand, F (2, 161) = 3.931, p = .022, ηρ² = .047. Follow up
pairwise comparison indicated that participants who viewed the ad with White cultural
cues (M = 3.57, SD = 1.00) reported significantly higher attitudes toward the product
compared to participants who viewed ads with Black cultural cues (M = 3.17, SD = 1.00,
p = .034), supporting H5a. However, the interaction between cultural cues embedded in
hashtag messages and ethnic identity was not significant, F (2, 161) = .174, p = .841, ηρ²
= .002. Thus H5b was not supported. Since none of the interaction effects were
significant, an additional Table 4.2 was added for means and standard deviations for the
five dependent variables as functions of cultural cues embedded within hashtag messages.
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Table 4.1
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Means and SDs for Study Dependent Variables as a Function of Cultural Cues and Ethnic Identity
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Table 4.2
Means and SDs for Study Dependent Variables as a Function of Cultural Cues
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7
Identification
Intended Audience
Aad
Apr
Abr
6
Mean Scores
5
4
3
2
1
0
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Figure 4.1
#AmericanPride
#BlackPride
Effects of Cultural Cues on Advertising Outcomes
Additional Findings
Influence of Hashtag Messages on Purchase Intentions
A two-way ANOVA was conducted to evaluate the effects of cultural cues
embedded in hashtag messages and ethnic identity on purchase intentions. The ANOVA
indicated a marginally significant main effect for cultural cues embedded in hashtag
messages on purchase intentions, F (2,161) = 1.819, p = .1, ηρ² = .022. The ANOVA
model also showed a marginally significant main effect for ethnic identity on purchase
intentions, F (1,161) = 2.610, p = .1, ηρ² = .016, however it was not the focus on the
study. The interaction between cultural cues embedded in hashtag messages and ethnic
identity was not significant, F (2,161) = 1.389, p = .252, ηρ² = .017.
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CHAPTER 5
CONCLUSION
Summary of Findings
This study was conducted as an initial test of whether cultural cues embedded
within hashtag messages can influence advertising outcomes. To review, cultural cues
embedded within hashtag messages that are consistent with ingroup status should lead
more positive responses to the advertisement outcomes, particularly for those who
strongly identify with their ethnic group. Following this prediction, it was hypothesized
that for White viewers, White mainstream cultural cues embedded within hashtag
messages should facilitate identification more so than Black cultural cues embedded
within hashtag messages. Further, because identification with a source is expected to
increase the persuasiveness of the source’s message (Kelman, 1961), advertisements
featuring White cultural cues embedded within hashtag messages were hypothesized to
result in more positive advertising outcomes (e.g. attitude toward the product) for White
viewers.
To test the hypothesized relationships, print advertisements were designed
containing hashtag messages indicating White mainstream cultural cue and Black cultural
cue, with another condition being no hashtag messages presented.
Findings from this study provide important insight into the effect of cultural cues
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embedded within hashtag messages in advertising outcomes. The data collected indicate
that participants in fact respond differently to advertisements depending on the hashtag
message they saw (whether White or Black cultural cues appeared in the advertisement).
As predicted by H1a, when the cultural cues embedded within hashtag messages that are
consistent with the White ingroup status, White viewers reported greater identification
with the advertising character. As predicted by H2a, White viewers perceived the
advertisement to be intended to people like them when White mainstream cultural cues
embedded within the hashtag messages were present compared to Black cultural cues.
Even though there were no significant findings indicating that ethnic identity had an
interaction effect with cultural cues embedded within hashtag messages on identification
and intended audience perspective in this study, the result still suggests that viewers
utilized background cues to make assessments of the advertisement. The fact that such a
small hashtag message did influence viewer attitudes toward the advertisements is an
important finding, as it indicates that when viewing advertisements, viewers tend to be
active audience. Thus it is crucial for practitioners to be highly cautious of how things as
small as a hashtag message in an advertisement can influence how viewers respond to the
advertisement.
This study was also concerned on how cultural cues embedded within hashtag
messages could influence advertising outcomes, particularly the three variables that of
concern to advertising practitioners and researchers—attitude toward the advertisement,
attitude toward the brand, and attitude toward the product. If the social identity theory
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framework was accurate in media context, then hashtag messages consistent with ingroup
status should lead to more positive advertising outcomes. Results indicated that indeed,
cultural cues embedded within hashtag messages had the ability to significantly impact
how reviewers responded to advertising media. Participants had more positive attitudes
toward the advertisement, the product, and the brand when they were exposed to the ad
featuring White mainstream cultural cues embedded within hashtag messages compared
to Black cultural cues. Even though it was not hypothesized based on the theoretical
framework, the finding of cultural cues embedded within hashtag messages can also
influence purchase intentions was fascinating. It showed that a hashtag message can not
only influence the attitude, but can also influence viewers’ behavioral intentions. It
reinforces the fact that advertising practitioners need to be mindful to things as small as a
hashtag message as the viewers definitely pay attention to it.
Overall, hashtag messages that are not consistent with the viewer’s perceptions
were found to lead to less favorable advertising outcomes. Study data show that
background cultural cues embedded within hashtag messages were used by participants
to help categorize and form impressions about the advertisement. Further, the hashtag
messages presented not only influenced how viewers perceived the advertisement, but
actually led to significant different ratings of the advertisement content. This finding has
significant implications for practitioners, with the increased popularity of Twitter and
hashtag, brand and product attitudes may be influenced not only by the texts of the
advertisement, but also by the cues within hashtag messages present in the advertisement.
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Limitations and Future Directions
Despite the significant findings of hashtag messages on advertising outcomes, there
are certain limitations of the study. One of the limitations lies in the cultural cue
conditions. On the one hand, this study utilized explicit race cultural cues (i.e. American
vs. Black) to see if it will influence White viewers’ responses to the advertisement. Future
research should examine whether more implicit race cultural cues embedded within
hashtag messages will result the same impact on White viewers’ responses. Since the
strength of ethnic identity did not interact with the explicit hashtag message cue, future
research should also examine if there will be an interaction effect using implicit cues. On
the other hand, there might be a potential confound for the hashtag message
#AmericanPride because it is not clear whether it elicited identification with Whiteness or
American patriotism for White viewers. In addition to measure ethnicity identity, future
research should also measure patriotic attitudes as a proxy of cultural identity to see how
advertising outcomes would be impacted. It is also unclear about the specific reasons why
the hashtag message #BlackPride elicited sense of disconnection for White viewers which
resulted in less favorable attitudes. It could be due to the sense of competition in sports
domain where Blacks have been dominant with the fact that there was a sprinter running
towards the sports drink in the advertisement. It could also be because they see this
hashtag message as separatist or even racism so that they feel discomfort with the
advertisement, which in turn affected the advertising outcomes. Future research should
address issue and explore under what conditions the sense of competition can be elicited
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for White viewers rather than other factors such as disconnection due to the message the
hashtag communicated to the viewers. Since the product featured in the advertisement is
from a domain where Blacks usually outshine Whites, future research should also
consider use different types of products, for example, a household product where there
may not be any sense of competition, or a product in the field of education where Whites
usually outshine Blacks. Future research should also consider adding a thought listing
task at the end of the questionnaire to ask participants about their thoughts and attitudes
based on the hashtag messages they saw, as well as what came to mind when they were
viewing the advertisement.
An alternative way to look at the results is that White viewers did not necessarily
prefer the advertisement featuring #AmericanPride but rather they just did not like the
one with #BlackPride as much, with the fact that White viewers did not rate significantly
different between #AmericanPride and no hashtag condition. So it may not be because of
the White cultural cue that elicit the favorable attitudes toward the advertisement and
subsequent responses, but rather because the Black cultural cue condition made White
participants think that they were not the intended audience for the advertisement thus
they feel disconnected with the product and brand. With an effort to reach the targeted
market (e.g. Blacks), practitioners should be highly cautious with cues that are specific to
the culture because Black culture cues may enhance sense of belonging and connection
for Blacks but at the same time unintendedly creating a disconnection with the
unintended audience like Whites.
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Another limitation is that this thesis did not include racial minorities as participants
to determine how they may be influenced by cultural cues embedded within hashtag
messages. While this study focused on White viewers, racial minorities are likely to
respond to advertisements with minority or White mainstream cultural cues differently.
As the United States’ racial makeup become more diverse, understanding how different
racial or ethnic groups respond to cultural cues embedded within hashtag messages is
crucial, especially for marketers who are interested in using hashtag messages to attract
consumers. Future research should address this issue and test how minorities respond to
hashtag messages embedded.
The study results point to the need for further investigation of cultural cues and
hashtag effects in advertising, as they appear more likely to affect advertising outcomes.
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Appendix A: Complete Study Questionnaire Instructions and Items
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This is a consent form for research participation. It contains important information
about this study and what to expect if you decide to participate.
Your participation is voluntary.
Please consider the information carefully. Feel free to ask questions before making your
decision whether or not to participate.
Purpose:
The purpose of this study is to improve our understanding of Twitter and hashtag usage.
You will be awarded with course credit for participation, as per your instructor’s extra
credit guidelines. Your participation is completely voluntary.
Procedures/Tasks:
For this study, you will complete an online survey using the online survey website,
Qualtrics. You will first be asked to complete a series of demographic questions. These
questions will ask you to tell the researchers your age, gender, race/ethnicity and your
current major. The researchers will not ask you to provide any personal information, such
as phone number or address. You will then be asked to complete a survey regarding
general understanding of Twitter and your Twitter usage. Based on your usage of Twitter,
you will be randomly assigned to one of the four advertisement conditions. After
browsing the advertisement, you will be asked a series of questions of 1) what you
thought of the advertisement, 2) your opinion on the product, and 3) additional questions
regarding hashtags and Twitter.
Duration:
This study will last about 20-30 minutes. You may leave the study at any time. If you
decide to stop participating in the study, there will be no penalty to you, and you will not
lose any benefits to THE OHIO STATE UNIVERSITY which you are otherwise entitled.
Your decision will not affect your future relationship with The Ohio State University.
Risks and Benefits:
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There are no risks in participating in this research beyond those experienced in everyday
life. As noted below, your responses will be confidential. Because this study uses an
online questionnaire, however, we are unable to guarantee complete Internet security as
42
transmissions can be intercepted and IP addresses can be identified. However, we will
make every effort to protect confidentiality of your information and the collected data
will be password-protected.
Confidentiality:
!
Efforts will be made to keep your study-related information confidential. However, there
may be circumstances where this information must be released. For example, personal
information regarding your participation in this study may be disclosed if required by
state law. Also, your records may be reviewed by the following groups (as applicable to
the research):
• Office for Human Research Protections or other federal, state, or international
regulatory agencies;
• The Ohio State University Institutional Review Board or Office of Responsible
Research Practices.
Incentives:
You will be awarded extra course credit as agreed upon by your instructor.
Participant Rights:
You may refuse to participate in this study without penalty or loss of benefits to which
you are otherwise entitled. If you are a student or employee at Ohio State, your decision
will not affect your grades or employment status.
If you choose to participate in the study, you may skip any questions that you feel
uncomfortable answering. Additionally, you may discontinue participation at any time
without penalty or loss of benefits.
Contacts and Questions:
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For questions, concerns, or complaints about the study, or you feel you have been harmed
as a result of study participation, you may contact Dr. Osei Appiah at [email protected]
or 614-292-6927. For questions about your rights as a participant in this study or to
discuss other study-related concerns or complaints with someone who is not part of the
research team, you may contact Ms. Sandra Meadows in the Office of Responsible
Research Practices at 1-800-678-6251.
Please indicate your agreement to the following statement:
“I have read this form and I am aware that I am being asked to participate in a research
study. I voluntarily agree to participate in this study.”
• ___ I agree
• ___ I do not agree
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Thank you for participating this study!
We would like to know some information concerning your background. Please be as
specific as possible when you give your answers. As previously mentioned, your
answers are anonymous.
1.
What is your major? _________________________
2.
What year/class are you in school?
______ freshman
______ sophomore
______ junior
______ senior
______ graduate student
______ Other (explain) _____________________________
3. Are you male or female? Male___ Female____
4. How old are you (age as of today) ?_______
5. What ethnicity do you identify with? ____
(1) Asian or Asian American, including Chinese, Japanese, and others
(2) Black or African American
(3) Hispanic or Latino, including Mexican American, Central American, and others
(4) White, Caucasian, Anglo, European American; not Hispanic
(5) American Indian/Native American
(6) Mixed; Parents are from two or more different groups
(7) Other (write in): _____________________________________
Now, we would like to know your general understanding of Twitter and your Twitter
usage.
1. Have you used Twitter before (e.g. look up a celebrity’s Twitter account)?
Yes___
No___ (if No, please skip questions #2-31, and go to question #32)
2. Do you have an account with Twitter?
Yes___
No___
3. How do you get on Twitter? (check all that apply)
A. Mobile Device (including cell phones, smart phones, tablet, etc.) _____
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B. Laptop _____
C. Computer at school _____
D. Computer at home ____
E. Other (please list) _____
4. Please rank your answers for question #3 in terms of the frequency (e.g. put A first if
you use Mobile devices to get on Twitter the most)
1) ____
2) ____
3) ____
4) ____
5) ____
The next set of questions are regarding reasons why you use Twitter and enjoyment
you have gained by using Twitter.
Instructions: Please answer the following questions using the range 1=Strongly Disagree,
2=Mostly Disagree, 3=Somewhat Disagree, 4=Neutral, 5=Somewhat Agree, 6=Mostly
Agree, 7=Strongly Agree
6. I use Twitter to make a purchase through business’s verified account ___
7. I use Twitter to comment on product I’ve heard about ___
8. I use Twitter to explore new sites ___
9. I use Twitter to surf for fun ___
10. I use Twitter to get information I need ___
11. I use Twitter to find out things I need to know ___
12. I use Twitter to message other people ___
13. I use Twitter to connect with my friends ___
14. I use Twitter to communicate with others ___
15. I use Twitter to follow celebrities ___
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16. I use Twitter to follow businesses or organizations ___
17. I use Twitter to kill time ___
because it is entertaining ___
because I enjoy it ___
because it is fun ____
because it relaxes me ___
to get away from pressures and responsibilities ___
to get away from what i am doing ___
to put off something I should be doing ___
18. I use Twitter to thank people ___
to let people know I care about them ___
to show others encouragement ___
to help others ___
to show others that I am concerned about them ___
19. I use Twitter to not look old-fashioned ___
20. I use Twitter because I need someone to talk to or be with ___
because I just need to talk about my problems sometimes ___
to forget about my problems ___
21. I use Twitter to make friends of the opposite sex ___
to be less inhibited chatting with strangers ___
to meet people (new acquaintances) ___
22. I get social information through Twitter ___
23. I use Twitter so that I feel involved with what’s going on with other people ___
24. Twitter is part of my everyday activity. ___
25. I am proud to tell people I’m on Twitter. ___
26. Twitter has become part of my daily routine. ___
27. I feel out of touch when I haven’t logged onto Twitter for a while. ___
28. I feel I am part of Twitter community. ___
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29. I would be sorry if Twitter shut down. ___
30. Approximately how many people are you following on Twitter?
a. less than 10
b. 10 to 50
c. 50 to 100
d. more than 100
31. In the past week, on average, approximately how much time PER DAY have you
spend actively using Twitter?
a. less than 2
b. 2 to 4
c. more than 4
We would also like to know your understanding about hashtag.
32. Do you know about Hashtags# in Twitter?
Yes ___
No ___
33. Have you ever used a hashtag before in your tweets?
Yes ___
No___
34. Have you ever searched for a hashtag in the search bar of Twitter?
Yes ___
No ___
35. If yes in question #34, in what situation did you do that?
Please list ___
36. Have you ever clicked a hashtag on tweets from other people?
Yes ___
No ___
37. If yes in question #36, in what situation did you do that?
Please list ___
Now, you will be shown one print advertisement. Please take a moment to look at
the entire advertisement, and answer the following questions the best you can.
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Based on your reviewing of the advertisement, please answer the following questions
using the range 1=Strongly Disagree, 2=Mostly Disagree, 3=Somewhat Disagree,
4=Neutral, 5=Somewhat Agree, 6=Mostly Agree, 7=Strongly Agree
38. The ad is good ___
39. The ad is interesting ___
40. The ad is informative ___
41. The ad is appropriate ___
42. The ad is easy to understand ___
43. The ad is objective ___
44. The ad is distinctive ___
45. The ad is inappropriate ___ ( R )
46. The ad is offensive ___ ( R )
47. The race/ethnicity of the character in the advertisement is...(please circle your answer)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Asian, Asian-American, Pacific Islander
Black or African-American
Hispanic or Latino
White, Caucasian, European, not Hispanic
American Indian or Native American
Biracial or Multiracial
Can’t tell/Don’t know
Don’t remember
48. What is the name of the brand? (If you don’t remember, please write down DR)
______
49. Please list the hashtag message you see in the advertisement. (If there is no hashtag,
please write down N/A) __________
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50. Please rate, on a four-point scale, how likely it would be that you would purchase
_________ “the next time you needed a product of this nature.”
1= “I definitely would not buy it”
2= “I might or might not buy it”
3= “I would probably buy it”
4= “I would definitely buy it.”
51. Please list some of the reasons why you intend to purchase or not to purchase this
product _________________.
Please also rate your overall impression of the product on four seven-point semantic
differential (-3 to 3 scale)
52.
Bad
Good
53. Unsatisfactory
Satisfactory
54. Unfavorable
Favorable
55. Dislike
Like
Based on your reviewing of the advertisement, please answer the following questions
regarding the brand. 1=Strongly Disagree, 2=Mostly Disagree, 3=Somewhat Disagree,
4=Neutral, 5=Somewhat Agree, 6=Mostly Agree, 7=Strongly Agree.
56. This brand’s product claims are believable.
57. This brand has a name you can trust.
58. This brand has the ability to deliver what it promises.
59. Knowing what I’m going to get from this brand saves me time shopping around.
60. This brand gives me what I want, which saves me time and effort trying to do better.
61.I need lots more information about this brand before I’d buy it. ( R )
62. I would never buy this brand. ( R )
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63. I would seriously consider purchasing this brand.
Now, please answer the questions of possibility of using Twitter in future.
64. If you have used Twitter before, will you use Twitter more in the future?
A. Yes
B. No
C. N/A
65. If you have never used Twitter before, will you start using Twitter?
A. Yes (go to question #66)
B. No
66. If you answered yes to question #65, will you register to be a Twitter user?
A. Yes
B. No (go to question #67)
67. If you answered no to question #66, will you use Twitter to look up information?
A. Yes
B. No
Lastly, we would like to know a little bit more about your cultural background.
Please use the numbers below to indicate how much you agree or disagree with each
statement: 1 (strongly disagree), 2 (disagree), 3 (agree), and 4 (strongly agree).
68. I have spent time trying to find out more about my ethnic group, such as its history,
traditions, and customs.
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69. I am active in organizations or social groups that include mostly members of my own
ethnic group.
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70. I have a clear sense of my ethnic background and what it means for me.
71. I think a lot about how my life will be affected by my ethnic group membership.
72. I am happy that I am a member of the group I belong to.
73. I have a strong sense of belonging to my own ethnic group.
74. I understand pretty well what my ethnic group membership means to me.
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75. In order to learn more about my ethnic background, I have often talked to other
people about my ethnic group.
76. I have a lot of pride in my ethnic group.
77. I participate in cultural practices of my own group, such as special food, music, or
customs.
78. I feel a strong attachment towards my own ethnic group.
79. I feel good about my cultural or ethnic background.
Thank you so much for participating in this survey.
Please create a random code to identify your data, if you decide to withdrawal your data.
We recommend that you generate the code using the last two digits of the year you were
born, the last two numbers of your driver’s license or other identification, and the last two
of your zip code. This allows for a secret code that only you know. You may also use any
code you like as long as you remember it. The researchers have no way of linking this
code to you. This will allow you to remove your data at a future time, if you so choose.
___________________
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