1. Influence in Online Media: A Study and Comparison of
Online and Offline Opinion Leadership in Fashion
Alicia Gil Houselog
School of Journalism and Mass Communication,
University of Minnesota
Spring, 2009
Abstract: An online questionnaire was conducted to investigate opinion leadership in
the field of fashion and its transition into the online environment. With 92
completed responses, the study found 19% of the total population could be
considered fashion opinion leaders. This group reports a higher than average
amount of acquaintances than other groups. Fashion opinion leaders’ traditional
media usage is similar to non-leaders’, however they are more likely to share fashion
advice and information through online channels, suggesting that fashion opinion
leaders are more likely to shift influence online than non-leaders. A subgroup was
also pinpointed: online sharers. This group makes up only 3% of the entire
population, but differentiates more in their media usage from non-leaders. They
also, by definition, are more likely to share fashion information across a number of
online vehicles than the fashion opinion leaders and non-leaders. The results
indicate that marketing of fashion designers and companies may benefit from
overweighting their marketing media vehicles to those that are predominantly used
by online sharers.
The current economic recession has implications on how companies market their
products and services to their consumers. It has shown that as companies cut their
budgets, advertising spending usually loses its funding first. (LA Times, 2009; New York
Times, 2009) With minimal dollars put toward marketing their products and services,
companies must find ways to reach as many people for as little money as possible. One
proposed technique is to find the people who influence the behavior of others like a
trickle down effect, also known as “opinion leaders” or “Influentials.” (Summers, 1970)
In the growing world of online media, where a vast array of networks are buzzing about
products and services, few studies have examined how these Influentials translate from

2. offline into the online space. (Rhee et. al, 2007) I will examine how we find these
opinion leaders, who they are, and what they do in online and offline spaces.
To explore my research topic, I administered a survey that asked respondents
about their perceived level of influence on the topic of fashion. I chose to focus on one
specific topic because general influence is too broad of a topic for what I am trying to
understand. Fashion seemed to be a good choice, considering I knew that I would
probably reach a majority of younger respondents. I used standard questions that
centered on face-to-face influence, demographic questions, media usage and leisure
activities, and also questions that were geared to online interpersonal communication.
But first, I looked into previous academic research and media coverage of general
influence, and well as fashion opinion leadership, both online and offline.
LITERATURE REVIEW
Katz & Lazarsfeld
In 1955, Elihu Katz and Paul Lazarsfeld wrote a book called called, Personal
Influence: The Part Played by People in the Flow of Mass Communication. In it, they
found a group they identified as opinion leaders. Mass media creates messages that reach
these leaders, who then spread that message to others. This process is what Katz and
Lazarsfeld refer to as the “two-step flow.” Opinion leaders are everyday people who are
not running formal groups, but rather speak on an informal basis, guiding opinions and
changes. Much of the time, they are not aware that they are even being influential. (Katz
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3. and Lazarsfeld, 1955, p. 138)
There are three subgroups to opinion leaders, according to Katz and Lazarsfeld:
Generally Influentials, Specific Influentials, and Everyday Contacts. Generally
Influentials are those that influencees trust to keep them updated on what is going on in
the world. Specific Influentials offer specific advice at a specific time. Everyday
Contacts are those who influencees continually talk to about news and popular culture
before they make decisions about purchasing or beliefs. (Katz and Lazarsfeld, 1955, p.
140-143) Katz and Lazarsfeld examined the relationships that these types of opinion
leaders had with the ones they gave advice to.
Relationships of Respondents and Three Types of Influentials
Everyday Specific General
Relationship Contacts Influentials Influentials
Non-family 15 34 51
Family 84 64 48
Parent 21 17 18
Husband 53 32 18
Other relatives 10 15 12
No answer 1 2 1
Total (=100%) 136 136 136
*Katz and Lazarsfeld, 1955, p. 144
Over half of the Generally Influentials seem to be outside of the family circle,
while only 34% of Specific Influentials and 15% of Everyday Contacts are outside of the
family. (Katz and Lazarsfeld, 1955, p. 144) However, when deciding whom to focus on
in their study, Katz and Lazarsfeld chose to ignore General Influentials, because of the
likely distance between these experts and the influencees, as well as the Everyday
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4. Contacts, due to the fact that their advice is not heavily tied to the decisions made by the
influencee. By focusing on Specific Influentials, they were able to study people who are
accessible to influencees, and who have shown significant powers of persuasion in a
memorable setting.
Katz and Lazarsfeld believed there are two different ways to identify Specific
Influentials: self-detection and description by the influencee. They first used self-
detection as their chosen technique, and then used follow-up interviews with the people
that the respondents claimed to influence to corroborate the validity of the initial study.
Overall, nearly two thirds of respondents confirmed that the influential occasion
occurred, 21% could not remember, and only 14% denied it. (Katz and Lazarsfeld, 1955,
p. 158) Due to these numbers, Katz and Lazarsfeld deduced that self-detection was not
only a convenient method, but also a reliable one.
One of the areas of interest for Katz and Lazarsfeld was the influence of people in
the topic of fashion (i.e. hair, makeup, clothes). In their interviews with women, they
found fashion opinion leadership to be highest among young unmarried girls, but that it
also appears in all life cycles. (Katz and Lazarsfeld, 1955, p. 251) There was some
evidence that higher social status leads to a more likelihood of influence, however, that
data was not completely clear. Influentials and influencees were most likely similar in
age and social status, showing that women generally look to those similar to them when
looking for fashion advice. (Katz and Lazarsfeld, 1955, p. 270)
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5. Gladwell
45 years after Katz and Lazarsfeld wrote Personal Influence, Malcolm Gladwell
expanded opinion leader research with his book, The Tipping Point: How Little Things
Can Make a Big Difference. In his second chapter, called the “Law of the Few,” he
states that even in our technology-driven, advertising-cluttered age, word-of-mouth is the
most important form of human communication. (Gladwell, 2000, p. 32) But who is
spreading these messages to others? Gladwell looked closely into a study done by
Stanley Milgram to answer this question.
In 1960, Stanley Milgram set out to see how we are all connected to each other.
He had 160 people from across the United States send a letter to a specific individual,
whom they did not know, through their various network of friends or acquaintances. His
results showed that there were, on average, six degrees of separation between the
individual who sent the letter and the one who, in the end, received it. However, what
was more important for opinion leadership studies was that Milgram found not all of the
people were as equal in importance as a select few. In fact, of the twenty-four letters that
actually made it to the end person, sixteen arrived from the same person. Gladwell
explains that this person is what he calls a “connector.”
Connectors are the people who attach us to the rest of the world and introduce us
to other social groups. They know an abnormally large amount of people. (Gladwell,
2000, p. 38) In reality, connectors enjoy the experience of keeping tabs on acquaintances
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6. and meeting new people; an area of interest not held by the general population.
(Gladwell, 2000, p. 46) Connectors also are connected to the “right” people. They
“occupy many different worlds, subcultures and niches” (Gladwell, 2000, p. 48) in order
to know the right person for every future need they may encounter. Gladwell states that
these connectors do not need to be friends of the influencee in order to be opinion
leaders. In fact, people are usually not exposed to new ideas through friends because
they oftentimes live in the same subculture or world as them. Because connectors strive
to live in as many worlds as possible, they can be a field of expertise on many subjects
that average friends are not aware of. (Gladwell, 2000, p. 54)
But Gladwell does not posit that connectors are the only important factor in the
flow of influence. He believes that the people who spread the message to these
connectors are also integral to the process. He refers to these people as information
specialists, or mavens. (Gladwell, 2000, p. 59) Mavens are people who are drawn to the
accumulation of knowledge. (Gladwell, 2000, p. 60) They are not passive in their
collection of information, and they know how to get a deal and are more than willing to
share that knowledge with others. They know things that the majority of people do not
because they read more magazines, newspapers, and in some cases, more junk mail than
others. (Gladwell, 2000, p. 67) Mavens are not persuaders. They serve to educate those
around them, and to gain knowledge as well, not to push an agenda. (Gladwell, 2000, p.
69)
Finally, Gladwell recognizes a third group of people who affect influence:
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7. salesmen. These are the people who, unlike the mavens, do try to persuade the
unconvinced. (Gladwell, 2000, p. 70) They have a natural exuberance and charm that
makes them likeable to many people. Mavens also hold many nonverbal cues, such as
smiles or nods, in their arsenal, which have shown to be quite persuasive on peoples’
thoughts and feelings. (Gladwell, 2000, p. 79) Gladwell took a deeper look into how
salesman can be so persuasive.
Gladwell likens a face-to-face conversation to an “elaborate dance” where
speakers and listeners “dance” to microcurrents of a speech. These microcurrents can be
body movements, facial expressions, volume or pitch shifts, or any given change that a
person subconsciously uses to persuade their listener. (Gladwell, 2000, p. 82) This
“dance” forms a bond between the speaker and listener, which is what makes salesman so
effective. They have the natural, uncontrived, ability to get their listeners to trust them.
The roles of connector, maven, and salesman are not mutually exclusive.
Gladwell points out that one of the reasons why Paul Revere’s midnight ride was so
successful was because he was not only an avid collector of information (maven), but
also held a great network of acquaintances (connector). (Gladwell, 2000, p. 59)
Therefore, to be a connector does not diminish your chances of being a maven or a
salesman. In fact, it is plausible that one could be all three.
Berry & Keller
In 2003, Jon Berry and Ed Keller studied RoperASW data on what were referred
to as Influential Americans, or the Influentials. These people make up ten percent of the
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8. United States population (Berry & Keller, 2003, p. 28) and know many people whom
they see throughout the week. This constant communication creates a multiplier effect,
as those whom they influence spread the message to others and accelerate trends. (Berry
& Keller, 2003, p. 29) Influentials are the ones who initiate the trends. They are
considered the “early majority” whose conversations with others actually shape behaviors
and attitudes of society. (Berry & Keller, 2003, p. 31) Influentials are not just the
celebrities who seem to start trends, like Oprah or Madonna, they are everyday people
that surround us, like neighbors, family, and friends. In fact, there seems to be national
skepticism surrounding top-down influence from celebrities and politicians, as Americans
do not think that these figures are relevant to their lives. (Berry & Keller, 2003, p. 30)
According to Berry and Keller, Influentials share some general characteristics.
They have an activist approach to life and their network is broader than general society’s,
as well as the “demographically desirables” (i.e. the affluent). They are often looked to
for advice and are avid problem solvers and trendsetters. (Berry & Keller, 2003, p. 31)
Demographically, there are central characteristics that the authors discovered, yet they
stress that demography is not as strong of an indicator as the more psychographic
characteristics. They found that Influentials are more likely to have had some college
education, are in mid-life (median age is 45), they are in child-rearing years, are at middle
to upper-middle income levels, and are at positions of responsibility at work. Berry and
Keller also found that the gender split of influence is half and half. (Berry & Keller,
2003, pgs. 31-35)
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9. Demographics: Who Is the Typical Influential?
A man or a woman (50% each)
Middle-aged
. . . . 45.2 years old for median (+2.3 years from the total public)
Middle/upper-middle class
. . . . $55,300 median household income (+$17,900 from the total public)
College educated
. . . . 80% have attended college (+30 points from total public)
. . . . 49% are college graduates (+26 points from total public)
Married with children
. . . . 70% are married (+13 points from total public)
. . . . 53% with children at home
Homeowners
. . . . 74% own their own home
Employed
. . . . 72% are in workforce
. . . . 58% in full-time job
Executive or professional
. . . . 34% as the leading occupation (+19 points from total public)
*Berry & Keller, 2003, p. 35. Source: Roper Reports
The most strong indicators of Influentials, however, are activism, being plugged
in, having impact, possessing an active mind, and trendsetting.
Activism
Activism is the most identifying characteristic of Influentials. Influentials are
more likely to be involved in their communities with activities like attending town hall or
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10. school board meetings or serving on the board of a local organization. (Berry & Keller,
2003, pgs. 39-40) They volunteer more than the general public and are political active.
(Berry & Keller, 2003, p. 41) They are also less involved in passive activities for leisure,
such as television or movie viewing or video games, but rather choose to exercise, take
trips, read, volunteer, or browse the Internet. (Berry & Keller, 2003, p. 42.)
Plugged In
Influentials are plugged in, or connected to groups and people. In fact, they have
a significantly larger number of ties to more groups of people than the average American.
(Berry & Keller, 2003, p. 47)
Plugged In: Connected to Many Communities
Percentage of Influentials saying they feel at least “some” connection to group, with point
difference from total public (percentage who feel “strong connection.”)
At least “some” Point difference “Strong” connection,
connection point difference
Neighborhood or town 96% +7 (63%, +21)
Religious or spiritual 85% +6 (59%, +14)
group
Workplace 72% +7 (51%, +12)
Political Group 58% +29 (22%, +13)
Alumni association for 57% +28 (20%, +10)
college or school
Group for hobby, 57% +22 (22%, +10)
interest
Youth-related group 53% +22 (29%, +16)
Social 47% +26 (25%, +17)
activism/volunteer
group
Professional group or 43% +21 (25%, +14)
union
Ethnic group 34% -2 (14%, --)
Demographic group 33% +2 (9%, -2)
Support group 22% +5 (10%, +2)
Virtual/online 22% +6 (8%, +4)
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11. community
Gay/lesbian 8% +1 (2%, --)
*Berry & Keller, 2003, p. 49. Source: Roper Reports
It seems that Influentials particularly outweigh the connections of the average
citizen in political groups, alumni associations, activist and volunteer groups. They are
also much more likely to have ties with hobby, youth-related, and professional groups.
Impact
According to Roper Reports, Influentials are twice as likely as average Americans
to be asked for advice on a variety of topics. (Berry & Keller, 2003, p. 52) They are not
experts on every single topic, but are more looked to for their opinions on certain subjects
than others. In the field of fashion, which is what I will focus on for this study, the
average Influential is not turned to for advice, however, Berry and Keller said that it is
because young adults seem to dominate that area. (Berry & Keller, 2003, p. 52) Perhaps
it would be more effective to investigate younger opinion leaders in that topic, as people
aged 18-29 are twice as likely as the average Influential to be asked about fashion advice.
(Berry & Keller, 2003, p. 54)
Active Minds
Influentials are more engaged than the average person. They look for information
and desire knowledge. (Berry & Keller, 2003, p. 58) They have high levels of interest in
a wide variety of subjects. Berry and Keller found Influentials to be significantly more
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12. interested in politics, science, history, war, and technology than the total public. (Berry &
Keller, 2003, p. 59)
Trendsetting
The final distinguishing trait of Influentials is their role as pioneering consumers.
For example, they were among the first to own a personal computer, recognize the
potential of the Internet, utilize automatic teller machines, and purchase VCRs. (Berry &
Keller, 2003, pgs. 65-66) It is not that Influentials buy more products than the average
consumer, they just have an innate curiosity that leads them to find trends and spread the
word to others.
Rhee, Kim & Kim
Rhee et. al conducted a study on Influentials’ role in online communications in
2007. They identified four different roles of the online population: general online
discussants, quiet persuaders, attention gatherers and online opinion leaders. (Rhee et. al,
2007, p. 13) General online discussants made up 77.9% of the online population. They
participate in discussions online, but do not receive attention from other online
occupants. Quiet persuaders, 4.4% of everyone online, do not receive much attention
from other occupants, but receive positive mentions about their messages, unlike general
online discussants. Attention gatherers (6.9% of online population) receive attention
from other discussants, but not positive attention, so they are not deemed influential. On
the other hand, online opinion leaders, which make up 10.8% of the online population,
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13. are viewed as influential because they receive much positive attention from other
discussants.
The demography of online opinion leaders leans toward educated males. Online
opinion leaders have also been found to read and write more on the Internet than the
online general public. Also, according to the study’s content analysis of discussions
made online, online opinion leaders (as well as attention gatherers) have been found to
have a higher level of argument quality in their messages and are more competent in
Internet communication. (Rhee et. al, 2007, p. 19) Politically, they lean slightly liberal
and extreme, they have a higher level of political efficacy and they participate more in
civic activities. Other than the left-leaning political characteristic, this information is
consistent with offline opinion leader research. (Rhee et. al, 2007, p. 19) These online
Influentials consume newspapers and television more actively than the general online
population. They also have high consumption rates for the Internet, however, their high
rate of Internet information gathering does not set them apart from the online general
public. Overall, the demographic and psychographic characteristics of online opinion
leaders did not seem to differ much from offline opinion leaders. However, it is possible,
according to the authors, that the anonymity of the Internet providing a more equal
chance for sharing opinions no matter what a discussant’s age, gender, socio-economic
status or education level is. (Rhee et. al, 2007, p. 19)
Summers
Finally, because we are focusing on online opinion leadership in the topic of
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14. fashion, I reviewed an offline study of fashion opinion leadership by John Summers. In
1970, he studied 1,000 women about their behaviors in spreading messages about
women’s clothing. He found that the upper 28% of his respondents to be classified as
opinion leaders. He also found them to be younger, more educated, have higher incomes
and higher occupational status than non-leaders. (Summers, 1970, p. 180)
Their media choices showed that radio listening, television viewing, and book
readership had no significant effect on whether they were considered fashion Influentials
or not. However, those who read magazines were much more likely to be categorized as
an opinion leader. (Summers, 1970, p. 181) For the fashion opinion leaders that did read,
it was mostly for entertainment purposes, not for informational purposes.
It is important to note, however, that this information focuses solely on women,
and disregards males as fashion opinion leaders.
LITERATURE WRAP-UP
Overall, past literature about opinion leadership and Influentials has been
scattered. Summers and Katz and Lazarsfeld focused solely on females in their studies,
so it is hard to determine what their statistics and characteristics of opinion leaders would
be among the entire population. However, they did both find the opinion leaders to be
younger and more educated than non-leaders. Summers also found magazine readership
to be the only significant factor with fashion Influentials, however, Rhee’s online opinion
leadership study suggests that those who influence others online do consume more
television and newspaper than other online discussants. So, how does male and female
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15. fashion opinion leadership translate into online spaces?
HYPOTHESES
When designing this study, I made six hypotheses about fashion opinion
leadership.
H1: Women will index higher than men for opinion leadership in fashion.
Although previous studies on fashion opinion leadership only focused on women
as respondents (Summers, 1970; Katz & Lazarsfeld, 1955), I would suppose women to be
more focused on fashion than their male counterparts. This, however, is solely based on
popular belief, so I shall factor this question into my study.
H2: Opinion leadership will index higher with younger adults.
General opinion leadership has been shown to index higher with mid-life
individuals. (Berry & Keller, 2003, p. 35) However, Katz & Lazarsfeld found that in the
specific topic of hair and fashion, young unmarried women were more likely to be
Influentials. (Katz and Lazarsfeld, 1955, p. 251) This leads me to speculate that perhaps
fashion is a topic different from general opinion leadership.
H3: Offline opinion leaders will be more likely to share fashion advice online
(through Social Networks, email, microblogs, blogs, etc.) than non-leaders.
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16. Because fashion opinion leaders are more likely to be asked for advice on
clothing and trends, it seems likely that they would share their opinions in the online
space. Growing numbers of websites, applications, and social networks make it easier to
share information with more people, so the Internet would likely facilitate sharing for
opinion leaders.
H4: Opinion leaders will report to have a higher than average number of friends.
Gladwell, in his definition of connectors, claims that opinion leaders know an
abnormally large amount of people. (Gladwell, 2000, p. 38) They live in as many worlds
as possible and therefore can have a diverse knowledge of many topics. (Gladwell, 2000,
p. 54) This thinking leads me to believe that people who are trusted as a good source of
fashion advice and who share information are most likely ones who are connected to a
large amount of people.
H5: Opinion leaders will index higher on volunteering/community service than
non-leaders.
Berry and Keller found that activism is the highest indicator of what makes an
Influential. (Berry & Keller, 2003, pgs. 39-41) Although this was about general opinion
leadership, I would guess that fashion opinion leadership would be no different.
H6: Opinion leaders will be more likely to use a variety of media forms often to
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17. gain information.
Previous studies have reported a higher engagement level between opinion leaders
and media. Influencers seem to have more active minds and desire accumulation of
knowledge, more so than the general population. (Berry & Keller, 2003, p. 58)
METHOD
In order to gain understanding about the topic of fashion opinion leadership and
its ties to the Internet, I administered a survey through www.esurveyspro.com. To give
respondents more incentive to answer the survey, I had them sign up for the chance to
win one of three $5 Target gift cards. This questionnaire was sent to my online network
of around 600 people and 98 of them responded. Of the 98 respondents, 92 finished the
entire survey. The desired respondents were a mixture of ages and genders.
Measurements
The survey was made up of nineteen questions. Some questions were yes and no
answer, and the rest were ordinal. The first section of the survey was dedicated to
identifying who opinion leaders were among the respondents. I used the same scale as
John Summers did in his fashion opinion leaders study among women, which was
developed by Everett Rogers. (Rogers, 1962) I only made one change to the seventh
question. I made it apply specifically to face-to-face communication, as I wanted to
differentiate between online and offline influence.
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18. Opinion Leader Scale
1. In general do you like to talk about fashion with your friends?
Yes _____1 No_____2
2. Would you say you give very little information, an average amount of
information, or a great deal of information about fashion to your
friends?
You give very little information
You give an average amount of information
You give a great deal of information
3. Compared with your circle of friends, are you less likely, about as
likely, or more likely to be asked for advice about fashion?
Less likely to be asked
About as likely to be asked
More likely to be asked
4. If you and your friends were to discuss fashion, what part would you be
most likely to play? Would you mainly listen to your friends’ ideas or
would you try to convince them of your ideas?
You mainly listen to your friends’ ideas
You try to convince them of your ideas
5. Which of these happens more often? Do you tell your friends about
fashion, or do they tell you about fashion?
You tell them about fashion
They tell you about fashion
6. Do you have the feeling that you are generally regarded by your
friends and neighbors as a good source of advice about fashion?
Yes _____1 No_____2
7. During the past six months, have you told anyone about some kind of
fashion (in person/face-to-face)?
Yes _____1 No_____2
The next section of questions focused on the respondents’ media usage and
interests. They were asked how often they used their leisure time to do certain activities.
These activities ranged from offline activities, like reading the newspaper, talking on the
phone, volunteering, and going to the movies, to online activities, such as writing/reading
blogs, checking email, shopping online, watching online television, etc. They ranked
these activities in an ordinal fashion, specifying whether they never, rarely, occasionally,
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19. or often did these activities in their free time. (Questions in Appendix A)
The third section had six yes or no questions that regarded online sharing among
respondents. We asked these questions to get an understanding about their patterns of
influence over the Internet.
Online Influence Questions
1. During the past six months, have you sent an online link (URL) to
someone regarding fashion?
Yes _____1 No_____2
2. During the past six months, have you emailed a friend to help them with
fashion choices?
Yes _____1 No_____2
3. During the past six months, have you used social networking sites
(Facebook/MySpace/etc.) to share fashion information?
Yes _____1 No_____2
4. During the past six months, have you written a blog post about fashion?
Yes _____1 No_____2
5. During the past six months, have you shared a fashion web page/blog
post via RSS feed readers (like Google Reader, Pheeder, etc.)?
Yes _____1 No_____2
6. During the past six months, have you microblogged (Twitter, Tumblr, etc.)
about anything regarding fashion?
Yes _____1 No_____2
Finally, I asked them for demographic information that would identify
respondents’ gender, age, income level and education. This might give us a deeper
understanding of who online opinion leaders are. (Questions in Appendix B) I also asked
them one last ordinal question:
Would you say you have a smaller than average number of
friends/acquaintances, an average amount of friends/acquaintances, or a
great deal of friends/acquaintances?
Less than average number of friends
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20. Average number of friends
More than average number of friends
When determining who is a fashion Influential, I focused on two of the questions
in the opinion leader scale: number three and number six. I only regarded people as
opinion leaders in the topic if they regarded themselves as more likely to be asked for
advice about fashion in comparison to their friends and if they had the feeling that their
friends regarded them as a good source of fashion advice. I chose these two
measurements specifically because an opinion leader, according to Berry and Keller, is
twice as likely to be asked for advice on certain topics. (Berry & Keller, 2003, p. 52)
Also, I chose the sixth question, about being regarded as a good source, because Rhee et.
al discovered a group of online discussants they called attention gatherers. (Rhee et. al,
2007, p. 13) These people often discuss online and are heard, but their message is viewed
in a negative way. I liken this to respondents who are likely to voice their opinion on
fashion, but are not regarded as a reliable source for the topic. Influence taking place
when a message is viewed as negative or unreliable is unlikely, and therefore I did not
include these individuals in the data set of fashion opinion leaders.
RESULTS
Of the 92 respondents, we found a total of 18 people who wrote that they were
more likely to be asked about fashion than their friends and who felt that their friends
would regard them as a good source on fashion. This 19.6% of the total public is whom
we deem as fashion opinion leaders. Here is what I discovered about opinion leadership
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21. among males and females in the field of fashion:
H1 - Women will index higher than men for opinion leadership in fashion.
Our survey suggests a small skew toward the female gender regarding fashion
opinion leaders. According to our data, females over index with opinion leadership with
an index of 109, while men under index with 61. (100 index being average.) However,
we must take into account that only 18% of our total public was male, so it was not a very
high sample. Of the total male respondents in my study, 11% were found to be fashion
opinion leaders. 21% of the female respondents were a part of this group.
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22. H2 - Opinion leadership will index higher with younger adults.
Because the majority of our respondents fell into the 18-24 age range, we cannot
be certain that our age data is significant. In fact, we only had 8% of our respondents
outside of that age range. An interesting finding, however, is that despite the high
percentage of 18-24 year olds, it was our 25-34 year olds that over-indexed to fashion
opinion leadership. (They had an index of 220, as opposed to an index of 98 for 18-24
year olds.) None of our three respondents who fell in the older age ranges (35+) reported
themselves as fashion opinion leaders, which suggests that Katz and Lazarsfeld were
correct in stating that older women are less likely than younger women to be fashion
opinion leaders. (Katz and Lazarsfeld, 1955, p. 251) Therefore, it appears that there may
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23. be a general trend toward the 25-34 year olds as being more influential in fashion, but as I
previously stated, we would need a bigger sample of older respondents to confirm.
H3 - Offline opinion leaders will be more likely to share fashion advice online (through
Social Networks, email, microblogs, blogs, etc.) than non-leaders.
According to my survey, it seems that hypothesis three is correct for the most
part. Fashion opinion leaders over-index in the online space (Sending link: 140, email:
165, blogs: 200, RSS feed readers: 169, and microblogs: 157), except for with the use of
social networking sites, in which they hold a similar index to the non-leaders and the
general public. This seems to suggest that offline opinion leaders are more likely to
transition into online opinion leaders, as they are 52% more likely to share a link than
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24. non-leaders.
As for which vehicle fashion opinion leaders are more likely to use online, it
seems that their number one choice is email. Social networking sites, such as Facebook
and MySpace, RSS feed readers, and microblogs all tie for second place, while writing
blogs come in last. Non-leaders seem to prefer social networks over all online sharing
vehicles, followed by email, then by microblogs and RSS feed readers. Writing blogs is
also their last choice when it comes to sharing fashion information online. These
outcomes might have been different, however, had we received a higher number of older
respondents for our survey.
H4 - Opinion leaders will report to have a higher than average number of friends.
56% of fashion opinion leaders report having a higher than average amount of
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25. friends or acquaintances. This far outweighs the less than 20% reported by non-leaders.
In fact, none of the opinion leaders reported less than average number of friends, which
also adds to our case that opinion leaders, in the field of fashion, seem to have a higher
amount of friends than the total public. This coincides with Gladwell’s notion of
connectors, who attach us to the rest of the world by knowing an abnormally large
number of people. (Gladwell, 2000, p. 38)
H5 - Opinion leaders will index higher on volunteering/community service than non-
leaders.
Fashion opinion leaders do seem to over-index in the act of volunteering or
community service. They are 41% more likely to donate their free time to such activities
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26. than non-leaders. This coincides with the findings of Berry and Keller, who found that
opinion leaders volunteer more than non-leaders. (Berry & Keller, 2003, p. 41)
H6 - Opinion leaders will be more likely to use a variety of media forms often to gain
information. (Appendix C)
The findings of our survey do not coincide with hypothesis number six. Although
we found that fashion opinion leaders are more likely to write blogs about fashion, it
seems that they are about as likely to read blogs as non-leaders. Online and broadcast
television watching, as well as newspaper readership, also seems to be about equal
among fashion opinion leaders and non-leaders. Non-leaders reported that they are 28%
more likely to read books than opinion leaders, which contradicts Berry and Keller’s
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27. discovery that Influentials read more than non-Influentials. (Berry & Keller, 2003, p. 43)
Fashion opinion leaders, however, are 45% more likely to read magazines than non-
leaders, which coincides with Berry & Keller’s findings about Influentials and Summer’s
findings about female fashion opinion leaders. (Berry & Keller, 2003, p. 43; Summers,
1970, p. 181) Therefore, it seems that fashion opinion leaders are not consuming more
media on average than the general public, just reading magazines more often.
Subgroup: The Online Sharers
I did find a very small subgroup among our fashion opinion leaders that I call the
online sharers. This group only makes up 3% of the total respondents, but has shown a
great interest in sharing fashion advice in online spaces. I identified online sharers by
narrowing the fashion opinion leader segment to those who have shared information over
3 or more different online vehicles in the past six months. On average, a fashion opinion
leader will use just over 1 vehicle to share fashion information. By looking at those who
use more vehicles, we can understand a smaller segment that uses the Internet heavily to
share fashion messages.
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28. Of the three respondents that fit into this subgroup, one was male and two were
female. Because the sample of subjects is much too small, we cannot determine whether
gender is a factor for online sharers in regards to fashion. All three report that they have
microblogged about fashion in the past six months, that they have emailed someone
advice about fashion, that they have more friends than average, and that they are 18-24
years old.
Online Sharers’ Leisure Life
Percentage who “often” do activity, with point difference from all fashion opinion leaders
(percentage who do it at least “occasionally”)
“Often” Point difference “Occasionally” point
difference from
fashion opinion
leaders
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29. Read Newspaper 0% -17 (67%, +23)
Listen to music 100% +11 (0%, -11)
Read books 33% -- (33%, -6)
Cook 33% -6 (33%, --)
Read magazines 33% -- (67%, +34)
Get prepared for work 100% +50 (0%, -33)
Spend time alone 33% +5 (0%, -56)
Spend time on hobbies 67% +50 (33%, -34)
Talk on the phone with 67% +6 (0%, -22)
family/friends
Make home 0% -- (0%, -17)
improvements
Eat out in restaurants 33% -6 (67%, +34)
Volunteer 0% -11 (0%, -28)
work/community service
Exercise, play sports 33% -28 (33%, +16)
Travel on the weekend 0% -6 (33%, -11)
Browse in stores 33% -6 (67%, +17)
Go to cultural events 33% +22 (0%, -22)
Check email 100% +11 (0%, -11)
Check social network 100% +6 (0%, -6)
Write for a blog 33% +27 (33%, +22)
Read blogs 100% +83 (0%, -22)
Microblog 100% +78 (0%, -11)
Shop online 33% +27 (67%, +28)
Watch TV 33% +5 (67%, +17)
Watch sports 0% -11 (33%, -6)
Watch online TV 67% +50 (33%, -6)
Watch videos 33% +5 (67%, +23)
Nap 0% -17 (0%, -33)
Go to movies 0% -6 (67%, +23)
Play video games 0% -- (0%, -11)
When looking at the online sharer’s leisure activities, there are some similarities
between them and all fashion opinion leaders. They both have similar response rates for
email, social network sites, and music. However, there are big differences in how the
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30. two groups pass their time. First off, two online sharers report that they rarely volunteer
and the other reports that they never do so. There is a 39 percent point gap between the
likelihood that fashion opinion leaders volunteer and the likelihood that online sharers
would. Also, while all fashion opinion leaders are less likely to read blogs than non-
leaders, our online sharers are 61% more likely to read blogs in their leisure time
(occasionally-often) than fashion opinion leaders. All three respondents stated that they
microblog “often,” which is much higher than the 22% of fashion opinion leaders who
claim to do the same. Online sharers also report a 44% higher level of online television
viewership than fashion opinion leaders. Online shopping seems to be a much larger part
of the online sharer’s leisure time, as well as writing blogs and reading magazines.
Fashion opinion leaders are 51% more likely to spend time alone (occasionally-often)
than online sharers, which is interesting considering online sharer’s large use of the
Internet.
DISCUSSION
From this study, we have learned that there is a group of fashion opinion leaders
that make up approximately 19% of the total public. Though they seem to skew more
female and younger, we cannot make definitive claims about that just yet. Fashion
opinion leaders are more likely to share information online that non-leaders, but share
equally on social networking sites. They report having a “more than average” number of
friends and acquaintances and participate in a higher amount of volunteer work. Their
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31. media usage only differs in the fact that they are more likely to read magazines and less
likely to read books.
I have also pinpointed a subgroup that I have called online sharers. This group
contains heavy users of online vehicles to disseminate fashion information and advice.
According to our results, only 3% of the total public is considered to be an online sharer.
If our results are accurate, they may hold marketing implications for how brands
interact with consumers. We have found that 19% of the general population considers
themselves to be fashion opinion leaders, so it seems likely that marketers would want to
target these groups in order for them to continue the two-step flow of communication
(Katz & Lazarsfeld, 1955) and spread the message to others. However, my results are a
bit troubling for marketing professionals because I found that the traditional media use by
fashion opinion leaders does not differ much from that of the non-leaders. Other than
magazine readership, fashion opinion leaders are as likely to read or view media in a
similar fashion, which makes it hard to pinpoint them in the advertising world. Perhaps
marketers can overweigh magazines that index high with fashion opinion leaders to reach
them more effectively.
Fashion opinion leaders do have distinctive online sharing habits in comparison
to non-leaders. It would be possible for them to be targeted using search and key words
in email portals. However, a lot of the online spaces where they share information are
not ad supported, like Twitter or blog posting sites, like Blogger. Although there are
fewer paid advertising opportunities on Twitter and Blogger, there is still a possibility to
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32. interact with fashion opinion leaders in a more social way, like tweeting back and forth
or creating widgets that they can insert onto their blog.
Either way, traditionally or online, if you post advertisements where fashion
opinion leaders are, you are likely not targeting them very precisely because their media
habits are so similar to non-leaders. This is where the online sharers come in. Though it
is a small segment of the population, they are 55% more likely to shop online and 44%
more likely to watch online television than fashion opinion leaders. (144% more likely to
shop online 104% more likely to watch online television than non-leaders.) They are
also 22% more likely to watch broadcast television than fashion opinion leaders and 34%
more likely to read magazines. Fashion opinion leaders read blogs at about the same
levels as non-leaders, but online sharers are 61% more likely to read blogs than these
groups. All of these vehicles provide an avenue for targeted messages to online sharers.
However, it is highly unlikely that any advertiser would be willing to put their
entire media budget into focusing on 3% of the entire population. This information
should probably only be used as an overweighting rationale for online spaces, magazines
and television. More research would also need to be done on specific blogs, television
shows, magazine titles, and online stores that online sharers prefer.
INFLUENTIAL THEORY CRITICS
Throughout this paper we have taken the theory of Influentials as a given. We
assumed that there were indeed a group of 10-20% of the population who have a larger
amount of influence and friends than others and that by targeting opinion leaders,
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33. marketers have the possibility to spark a trend. However, there are individuals who do
not believe that such a process is possible, or helpful.
Duncan Watts
One of these individuals is Duncan Watts, author of Six Degrees: The Science of
a Connected Age. He analyzed email patterns and found that people with the most
connections, or “superconnectors,” are not as crucial to person-to-person communication
as Gladwell and other previous scholars have found them to be. In fact, Watts states that
Stanley Milgram’s findings about connectors do not work in the real world because he
found that only 5% of messages are passed through “superconnectors,” and the rest are
passed through the hands of a variety of weakly connected individuals. (Fast Company,
2008) Watts claims that ordinary people start the majority of trends, or “epidemics,” as
Gladwell calls them.
In response to Watts’ findings, Ed Keller, the co-author of The Influentials, stated
that no previous scholars in the field of opinion leadership were claiming that Influentials
were the only important targets for messaging. In fact, Gladwell points to mavens, the
information gatherers who provide opinion leaders with the information to pass on to
others, as an essential piece to the process of influence. (Gladwell, 2000, p. 59) The point
that they were trying to make was that by mobilizing opinion leaders behind a message,
that message will spread quickly and more efficiently than if spread by non-leaders.
(Fast Company, 2008)
Watts’ own study actually confirmed Keller’s statement. He found that although
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34. it is more likely for the average Joe to start a trend, ones spread by Influentials spread
much further. (Fast Company, 2008) However, he also continued on to say that targeting
opinion leaders was not the most effective way to pitch an idea. He claimed that you
“cannot will a trend into existence by recruiting highly social people.” (Fast Company,
2008) Therefore, he concludes that the best way to sell a message is through mass
marketing.
I find Watts’ arguments interesting and very relevant considering their ties to the
online space. However, I do not believe that his study completely proves Milgram,
Gladwell, and all previous opinion leadership academics wrong. The Milgram study was
conducted using the postal service by means of a physical letter. Watts’ study focused on
the patterns of electronic mail. This distinction may seem insignificant if you assume
that influence online is essentially the same as influence offline, however we cannot be
certain. Perhaps Watts’ findings confirm a relatively low level of trendsetting power
through online resources, but that cannot automatically negate Milgram’s offline
findings. In order to fully refute Milgram’s study, one would have to perform it in the
offline space.
Also, although Watts’ study states that ordinary citizens start the majority of
epidemics, he states that messages spread through Influentials reach more people. This
gives marketers reasons to overweight media that index high with opinion leaders, as I
stated earlier in my findings. Marketers should not solely focus on Influentials through
niche targeting, but use that narrow targeting as a supplement to mass communication
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35. channels.
Bentley & Earls
Dr. Alex Bentley & Mark Earls also do not believe that a few well-connected
individuals have the ability to push trends into existence. On the contrary, they believe
that consumer behavior follows the act of copying, either randomly or directed, which
then leads to a pull strategy where consumers demand products from companies rather
than companies trying to push products upon consumers, like Katz and Lazarsfeld’s two-
step flow model. (Bentley & Earls, 2008)
Random copying is often a subconscious process made by everyone continually.
For example, by walking down the streets of London, one would encounter many
fashions and brands that they are likely to copy in order to feel included among the
stylish. (Bentley & Earls, 2008) Directed copying is more of a conscious behavior that
you can trace back to specific individuals. The most prevalent example is how the
majority of people can trace back political beliefs or laundry soap preferences to their
parent’s preferences. (Bentley & Earls, 2008) These forms of copying lead you to simply
ask for products that will give you inclusion among the groups that you surround yourself
with, which is a pull strategy.
Bentley and Earls do not suggest that Influentials do not exist. They just believe
that opinion leaders are a lot more rare than we think they are. Therefore, independently
generated actions do not guide our decision making, but rather collective group
purchasing behaviors. (Bentley & Earls, 2008)
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36. I have a problem with Bentley and Earls’ findings. Although they acknowledge
that Influentials exist, but are rare, they do not highlight the importance of Influentials in
creating the norms of the collective group. They make it seem as if those who we copy
were essentially born to favor certain brands or styles. In reality, it is more likely that
someone decided to wear a certain brand or style and then later were copied by their
acquaintances. Therefore, the two-step flow still seems to exist, just as a separate piece
from the process of copying. In order for the random or directed copying to exist, the
trend must exist, and Influentials are the individuals who are more likely to start such
trends, according to previous research. (Berry & Keller, 2003, pgs. 65-66)
I do agree with Bentley and Earls that companies should adopt tactics that include
visibility and participation with consumers (Bentley & Earls, 2008), especially with
younger generations who prefer a less authoritative marketing message and like to feel
that they are in some way connected to a brand. As the author of YouthQuake, James R.
Palczynski, said, “The old-style advertising that works very well with boomers, ads that
push a slogan and an image and a feeling, the younger consumer is not going to go for.”
(BusinessWeek, 1999)
LIMITATIONS
The biggest limitation to my research was the small sample size that I collected
for my survey. It would have been more telling had I been able to reach a broader
number of people and if I would have been able to get a more national reach. It is quite
likely that the majority of the respondents were from the Midwest United States, though
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37. that was not a question on the survey. However, with almost 100 respondents, I was able
to capture a small glimpse into the world of opinion leadership.
Another limitation was the fact that the majority of my network contacts are
between the ages of 18-24. Perhaps my administering of the survey through the Internet
limited my ability to reach older respondents, as they are less likely to be tethered to
technology than the younger generations. To reach an older audience, it may have been
more effective to make paper copies of the survey and hand them out.
Also, because the survey was administered online, it is likely that the respondents
are more adept at using technology, which may skew the online behavior findings of my
study. It is plausible to imagine that because I contacted these people through a social
networking site (Facebook), they may be heavier users of the Internet and social media
than the average person.
My sample was also much more highly educated than the general population of
the United States. Every respondent had some college experience, and over 40% had
either graduated from college or received a postgraduate degree. This most likely has
implications about technology uses, income levels, concentration of friends, and media
use.
Finally, although Katz and Lazarsfeld believe that self-designation is a reliable
test of opinion leadership (Katz & Lazarsfeld, 1955, p. 158), there are critics of such
technique. Self-designation relies on the respondent recognizing his or her own level of
influence, which can be a hard thing to judge. I took Katz and Lazarsfeld’s confidence in
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38. self-designation without question, so future research may benefit from follow-up
interviews with the influencees to ensure Influentials are exerted influence upon others.
FUTURE RESEARCH
There are many avenues of research that could extend from my findings. During
his discussion about salesmen, Malcolm Gladwell talked about the “dance” that occurs
between the influencer and the influencee, but do these microcurrents of nonverbal
communication occur online? If so, what online functions serve as the facial expressions,
pitch changes, etc. that make salesmen seem more approachable? Is there, in fact, no
dance that exists online, and if so, can salesmen exist online without it?
Another topic to address is whether or not number of readers or followers of
messages (on blogs and microblogs) has implications regarding influence levels. Are
online discussants gaining false credibility by padding their readership or grasping for the
greatest amount of friends, or are readership numbers and followers indicative of
persuasiveness?
Finally, is it possible that self-designation is not a sufficient model to use in
confirming opinion leadership online, as the “Influential” does not know if the
“influencee” even read the advice given unless he or she replies back? Perhaps an online
discussant believes that he or she is more influential than they actually are because of
their great number of tweets, emails, or blog posts, but in reality no one is paying
attention. This study would require more specific evaluations of post-advice situations to
ensure that the “Influentials” are actually being persuasive.
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39. CONCLUSION
In this economic climate, advertising agencies are continually trying to find ways
to spread their messages more efficiently, and the Influentials theory seems to pinpoint an
audience that can do that for them. With a push toward communication via the Internet,
advertisers need to know whether these opinion leaders exist in online spaces. In my
study of fashion opinion leadership, I found that they do. In fact, a hyper-sharing group
of online opinion leaders exists which I call online sharers. This group can act as a niche
supplemental target for advertisers, as they show media consumption levels that
differentiate from general fashion opinion leaders and non-leaders.
APPENDIX A
8. How often do you use your leisure time to do these things?
Often Occasionally Rarely Never
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40. Read newspaper
Listen to music
Read books
Cook
Read magazines
Get prepared for
work
Spend time alone
Spend time on
hobbies
Talk on the phone
with
family/friends
Make home
improvements,
repairs
Eat out in
restaurants
Volunteer work,
community
service
Exercise, play
sports
Travel on
weekends
Browse in stores
Go to cultural
events
Check email
Check social
network sites
(Facebook,
MySpace, etc.)
Write for a blog
Read blogs
Microblog (on
sites like Twitter,
Tumblr, etc.)
Shop online
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41. Watch TV
Watch Sports
Watch online TV
Watch videos
Nap
Go to movies
Play Video
Games
APPENDIX B
15. Gender
Male
Female
16. Age
Under 18
18-24
25-34
35-44
45-54
55-64
65+
17. Income Level
Under $20,000
$20,001-$50,000
$50,001-$75,000
$75,001-$100,000
$100,001 +
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42. 18. Education
Less than high school graduate
High school graduate
Some college
College graduate
Postgraduate degree
19. Would you say you have a smaller than average number of
friends/acquaintances, an average amount of friends/acquaintances, or a great deal
of friends/acquaintances?
Less than average # of friends
Average # of friends
More than average # of friends
APPENDIX C
Fashion Online Opinion Leader Media
Usage
Ofte
Activity n Occasionally Rarely Never
Read Newspaper 3 8 7
Listen to music 16 2
Read Books 6 7 5
Cook 7 6 4 1
Read Magazines 6 6 6
Get prepared for work 9 6 3
Spend time alone 5 10 2 1
Spend time on hobbies 3 12 2 1
Talk on phone with fam/friends 11 4 3
Make home improvements 3 13 2
Eat out in restaurants 7 6 5
Volunteer work/Community
service 2 5 7 4
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43. Exercise, play sports 11 3 3 1
Travel on weekend 1 8 7 2
Browse in stores 7 9 2
Go to cultural events 2 4 9 3
Check email 16 2
Check social network 17 1
Write for a blog 1 2 4 11
Read blogs 3 4 4 7
Microblog 4 2 3 9
Shop online 1 7 9 1
Watch TV 5 9 4
Watch sports 2 7 7 2
Watch online TV 3 7 7 1
Watch videos 5 8 4 1
Nap 3 6 6 3
Go to movies 1 8 7 2
Play Video Games 2 7 9
REFERENCES
Bentley, Alex and Mark Earls (2008), “Forget Influentials, Herd-like Copying is How
Brands Spread,” Admap, Vol. 43, No. 499, 19-22.
Berry, Jonathan and Edward Keller (2003), The Influentials, New York, NY: The Free
Press.
Fast Company January, (2008) “Is the Tipping Point Toast?”
Gladwell, Malcolm (2000), The Tipping Point: How Little Things Can Make a Big
Difference, Boston, MA: Little, Brown and Company.
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44. Katz, Elihu and Paul F. Lazarsfeld (1955), Personal influence: The Part Played by
People in the Flow of Mass Communications, Glencoe, IL: The Free Press.
Los Angeles Times, May (2009) “TV Networks are Uneasy about Declining
Advertising.”
New York Times, April (2009) “Newspaper Ad Revenue Could Fall as Much as 30%.”
Rhee, J., Kim, E. and Kim, H. (2007), “Exploring Online Opinion Leadership: A Validity
Test of the Concept in the Digital Age,” Paper presented at the annual meeting of
the International Communication Association, TBA, San Francisco, CA Online
2009, 02-04 from http://www.allacademic.com/meta/p173140_index.html
Summers, J. O. (1970), “The Identity of Women’s Clothing Fashion Opinion Leader,”
Journal of Marketing Research 7, 2: 178–85.
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