Influence in Online Media

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This was my summa cum laude thesis for my Bachelor of Arts in Strategic Communication. I compared people's reports of their influence in digital spheres to studies of opinion leadership in the …

This was my summa cum laude thesis for my Bachelor of Arts in Strategic Communication. I compared people's reports of their influence in digital spheres to studies of opinion leadership in the non-digital realm.

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  • 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 Houselog - 2
  • 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 Houselog - 3
  • 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) Houselog - 4
  • 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 Houselog - 5
  • 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: Houselog - 6
  • 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 Houselog - 7
  • 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) Houselog - 8
  • 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 Houselog - 9
  • 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) Houselog - 10
  • 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 Houselog - 11
  • 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, Houselog - 12
  • 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 Houselog - 13
  • 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 Houselog - 14
  • 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. Houselog - 15
  • 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 Houselog - 16
  • 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. Houselog - 17
  • 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, Houselog - 18
  • 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 Houselog - 19
  • 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 Houselog - 20
  • 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. Houselog - 21
  • 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 Houselog - 22
  • 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 Houselog - 23
  • 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 Houselog - 24
  • 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 Houselog - 25
  • 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 Houselog - 26
  • 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. Houselog - 27
  • 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 Houselog - 28
  • 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 Houselog - 29
  • 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 Houselog - 30
  • 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 Houselog - 31
  • 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, Houselog - 32
  • 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 Houselog - 33
  • 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 Houselog - 34
  • 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) Houselog - 35
  • 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 Houselog - 36
  • 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 Houselog - 37
  • 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. Houselog - 38
  • 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 Houselog - 39
  • 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 Houselog - 40
  • 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 + Houselog - 41
  • 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 Houselog - 42
  • 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. Houselog - 43
  • 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. Houselog - 44