UNIVERSITA’ COMMERCIALE LUIGI BOCCONI
                         FACOLTA’ DI ECONOMIA
         CORSO DI LAUREA SPECIALISTICA...
CONTENTS

When the “Mutes” start singing: a Consumer Behavior Perspective on Online Video Upload
and User Activation on Yo...
RESULTS                                                             59
DISCUSSION                                         ...
To Patience,


and to all those who have been patient with me,
                 who have been believing in me.
     I wish...
3


When the “Mutes” start singing: a Consumer
Behavior Perspective on Online Video Upload
and User Activation on YouTube
...
4

and theories of relational cohesion (Lawler and Yoon, 1996), advertising case histories,
market strategy (Prahalad and ...
5

Dholakia, 2002) and self-disclosure in computer-based environments (Moon, 2000; Joinson,
2001).
To the author’s best kn...
6

   -      Individual/group– specific feature, looking for significant behavioral, motivational
                        ...
7

traditional media is strong amongst US marketers. This explains the forecasted growth of
296% of user-generated content...
8


                             CONCEPTUAL FRAMEWORK
CONSTRUCTS AND MEASURES UNDERLYING VIDEO UPLOAD BEHAVIOR
By their ve...
9

       “responsibility” for a specific step in the development process, and
       “hands-on activities”, like hands– o...
10

The individual characteristics of a member’s willingness to participate consist of constructs
such as attitudes, perce...
11


       A definition of Virtual Community
The concepts of social network and virtual community have been found to be i...
12

perceive their behavior in terms of person-to-person, rather than person-to-machine
relationships (Joinson, 2001; Ligh...
13

  favor,” so that the usefulness of the website and the credibility of its content is nurtured and
  keeps growing in ...
14

been meaning trouble for Google itself, pushing it towards setting up a 24/7 video removal
service, co-operating with ...
15


                   RESEARCH DESIGN AND DATA ANALYSIS
This analysis is designed to rely on the insights derived from t...
16


        RESEARCH TOOLS
The Qualitative part of the research features two personal interviews, two focus groups and
tw...
17

  -     What matters “experientially” to such users when uploading/thinking of uploading
        videos on YouTube? Un...
18

   -     Context: Upload proclivity might also be significantly session– dependent, according
         to various diff...
19

but featuring a “Re: viral video title” title)- and interpretations, i.e. modifications of the task
proposed in the ma...
20

to (yet, unlike Bianca, not entirely part of) a “work machine” ideological mindset, which
might justify his need- made...
21

have pre-empted new subjects, topics, constructs or variables from emerging. It was better
to see what the participant...
22



The numbers summarize the importance and appreciation (1= highest, 4= lowest)
participants gave to the areas portray...
23

content. Different content implies different interests in using the website, and different
interests mean different at...
24

added or allowed, in an attempt to increase social connectivity. It could be explained
through the catchphrase “meetin...
25

First of all, it appears to serve best as a dynamic, moment– by– moment compass and should
therefore not be taken as a...
26

Gaetano, 22, Italy:
Sometimes when I go watch old goals scored by old soccer glories, or old episodes of
forgotten TV ...
27

The semiotic square is in wide use in cultural studies and it was developed in the late 80’s as
a way to analyze paire...
28

A further reason why the semiotic square has turned out to be a useful tool for the analysis
of statements regarding t...
29

Although the techtopian ideological pattern implies that some kind of technological sublime
can not only render observ...
30

wealth and success. The Work Machine ideology articulates technology onto collaboration,
productivity, efficiency.
The...
31

about what I am up to on the Facebook. And neither do I upload a lot of videos on YouTube. I
am definitely not the pro...
32

however, what she said about what we now can see as her own trip to the Techtopian end:
Honestly, there was just about...
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads
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When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads

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An experimental model to increase user participation to YouTube advertising.
A semiotic approach to the online upload phenomena and a practical application of key variables which promise to optimize the viralness of a YouTube ad.

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When the "mutes" start singing: an experimental model to increase user participation to YouTube viral ads

  1. 1. UNIVERSITA’ COMMERCIALE LUIGI BOCCONI FACOLTA’ DI ECONOMIA CORSO DI LAUREA SPECIALISTICA IN MARKETING MANAGEMENT WHEN THE “MUTES” START SINGING: A CONSUMER BEHAVIOR PERSPECTIVE ON ONLINE VIDEO UPLOAD AND USER ACTIVATION ON YOUTUBE Relatrice: Prof.ssa Emanuela PRANDELLI Controrelatrice: Prof.ssa Paola CILLO Tesi di Laurea Specialistica di: NICCOLO’ MARIA MORONATO Matr: 1176205 ANNO ACCADEMICO 2007/2008
  2. 2. CONTENTS When the “Mutes” start singing: a Consumer Behavior Perspective on Online Video Upload and User Activation on YouTube Research objectives and problem definition 4 User Generated videos and Marketing Investments 6 CONCEPTUAL FRAMEWORK 8 Constructs and Measures underlying Video Upload Behavior 8 On Social Networks and Virtual Communities 10 A definition of Virtual Community 11 YouTube as Social Network 12 RESEARCH DESIGN AND DATA ANALYSIS 15 Qualitative Analysis 15 Research Tools 16 Video “bouquet” 18 Video Bouquet Selection Criteria 18 User Journals 19 Key Findings from Interviews and Focus Groups 20 EXPERIENTIAL USAGE OF THE UG WEBSITE 21 PERSONAL PERCEPTION OF A VIDEO– UPLOAD ACTIVITY’S PAYOFF AND WEB 2.0 IDENTITY CONSTRUCTS 25 Moving beyond paradoxes: an introduction to the semiotic square 26 Web 2.0 identity types and pursued upload payoff 33 UPLOAD NARRATIVE STRUCTURE 35 Creative Punchline of the video 35 The mood-attributes of the video: offering experiences rather than laughs. 36 “Narrative relevance” 37 Key Findings from User Journal Submissions 38 DEPENDENCY OF UPLOAD PROCLIVITY FROM CONTENT AND/OR LENGTH OF BROWSING SESSION 38 Quantitative Analysis 40 Key tested variables and constructs 41 UPLOAD PROCLIVITY: A DEFINITION 42 VIDEO- RELATED VARIABLES: A PATH TO FOLLOW FROM MOOD TO INTENTIONAL SOCIAL ACTION 43 USAGE- RELATED VARIABLES: CONTENT APPEAL AS HOMOPHILY AND TIE STRENGTH, SERVICE AS “IT”/ “THEY” PERCEPTIONS. 44 IDENTITY- RELATED VARIABLES: SEMIOTIC SQUARE USER MINDSET PROFILING À LA KOZINETS. 48 Key results 51 CONSTRUCTS VALIDITY- FACTOR ANALYSIS 51 DISTRIBUTION OF DESCRIPTIVE VARIABLES 52 UPLOAD PROCLIVITY- LINEAR REGRESSION ANALYSES 54
  3. 3. RESULTS 59 DISCUSSION 61 Objectives of this Paper 61 Review of Literature 61 Qualitative Analysis- overview 62 FINDINGS OF QUALITATIVE ANALYSIS 64 Quantitative Analysis- overview 64 FINDINGS OF QUANTITATIVE ANALYSIS 64 Significant Findings 65 Indications and Suggestions for Marketing Practitioners and YouTube 66 YouTube: optimize frequency and revise ratings system 68 Limitations 69 Calls for future research 69
  4. 4. To Patience, and to all those who have been patient with me, who have been believing in me. I wish one day I could give it all back to you
  5. 5. 3 When the “Mutes” start singing: a Consumer Behavior Perspective on Online Video Upload and User Activation on YouTube NICCOLO’ MARIA MORONATO Activating customers through viral video campaigns is the main objective of YouTube advertisers. Only a few of them, however, understand how to appeal to new customers in an environment which seems to be dominated by behavioral variables different from the ones traditionally found in other Media. Google and its clients engage almost every week in campaigns to get more and more people to upload user-generated videos on YouTube, pumping up the channel’s average video responding rate. This work intends to expand the consumer behavior theoretical knowledge about the act of uploading videos. It also aims at providing marketers and website administrators with new insights and tools to maximize the number of video responses to a viral video campaign through consumer research. M arketing Management in the Age of the Proactive Individual is no easy game. Consumers have been blossoming in many different and multi-faceted ways so far, forcing Companies - which are, all in all, made of consumers as well - to allocate every nickel and every minute of their resources on listening to, and inspiring individuals and groups, both in business-to-business and business-to-consumer landscapes. The proliferation of digital technology has made it easier for people to create their own entertainment content, User Generated Content (UGC from now on). With consumer engagement the new law of the land, advertisers are therefore beginning to create their own expressions of brands (Morrissey, 2005). Digital technology convergence and widespread connectivity taken for granted, some sort of “mass creativization” appears as the newer species of the mass-customized and co-creative breed of new postmodern individuals. Philosophical (Benjamin, 1936; Lyotard 1979), Persuasion (Gardner, 1985; Batra & Stayman, 1990; Bakamitsos & Siomkos, 2004), Sociological (Castells, 1996) Psyhological (Csíkszentmihályi, 1996) and Strategic (Prahalad and Ramaswamy, 2004; Prandelli, Sawhney and Verona, 2005; Kalyanam, McIntyre & Masonis, 2007) discourses, explanations and portents for such an Age have been out there quite a long time, intriguing academics, executives and schools of college students with juicy insights and attractive hypotheses about the shape of the near future. However, it has not been long since the first few scientific consumer behavior researches on the “new” consumers have been unveiling an amazingly complex intersection of merging research strains such as positive psychology (Csíkszentmihályi, 1996), relationship theory
  6. 6. 4 and theories of relational cohesion (Lawler and Yoon, 1996), advertising case histories, market strategy (Prahalad and Ramaswamy, 2004; Prandelli, Sawhney and Verona, 2005; Kalyanam, McIntyre & Masonis, 2007) and consumer behavior studies (Herr, Kardes and Kim, 1991; Barki and Hartwick, 1994; Moon, 2000; Burson, Larrick and Soll, 2005). Almost every three to four weeks, new survey results on the UGC-based social networking websites are released. This trend has been growing stronger since the late Nineties, when the strategies of a handful of digital content creation Software Houses like Sonic Foundry (NYSE ticker: SOFO, now part of Sony Media Entertainment) and Propellerheadz started including prices and solutions for segments of self entertaining consumers that were much younger, less expert and yet just as motivated as most of the professional clients. The research community seems to be still unsure of what exactly drives people to respond to viral marketing campaigns by creating and uploading new personally-crafted original content. Moreover, behavioral segmentations of the target audience are still a hard task to tackle, due to the absence of a reliable theoretical background. It is obvious that mere material incentives are good candidates for making a “user-activation” marketing campaign quite successful from a quantitative point of view. Nonetheless, it is true that most of the smartest campaigns aimed at redefining a brand through customers by means of call-to-UGC video claims ran at zero costs. Gmail’s 2007 collaborative video is one of the most renowned instances of such assumptions. Furthermore, marketer-ignited viral UGC campaigns in no way can compare to the user participation levels scored by genuine user-to-user phenomena, such as the old Coke & Mentos videos, the Kawasaki Frontales ludicrous dances or Terra Naomi’s smash hit music video. Such facts do strongly suggest that there might be much more to find out about content upload behavior than what is displayed by the results of surveys administered to website visitors on a more or less regular basis. RESEARCH OBJECTIVES AND PROBLEM DEFINITION This research intends, first, to come out as useful for social networking Companies, advertisers and agencies in satisfying their need to predict on a “scientific” basis the future success of creative and communicational efforts put into viral marketing UGC-based campaigns (Dobele, Toleman and Beverland, 2005). Second, it provides an overview of some of the most interesting consumer behavior works applicable to a literary framework for research on social networking websites. Topics covered include customer creativity (McKeen, Guimaraes and Wetherbe, 1994; Morrissey, 2005; Berthon, Pitts, McCarthy and Kates, 2007), mood in advertising studies (Gardner, 1985; Goldber and Gorn, 1987; Bakamitsos and Siomkos, 2004), user participation (Barki and Hartwick, 1994; McKeen, Guimaraes and Wetherbe, 1994), place and identity in social networking (Joinson, 2001; Goodings, Locke and Brown, 2007; Brown, Broderick & Lee, 2007), social interaction/website interface relations (Light and Wakeman, 2001), viral messaging (Herr, Kardes and Kim, 1991; Dobele, Toleman and Beverland, 2005), role differentiation (Eguíluz, Zimmermann, Cela-Conde and San Miguel, 2005), individual/group performance in social networks (Sparrowe, Liden, Wayne and Kraimer, 2001; Bagozzi,
  7. 7. 5 Dholakia, 2002) and self-disclosure in computer-based environments (Moon, 2000; Joinson, 2001). To the author’s best knowledge, no such work of collection of literature consistent with a behavioral perspective on content upload to social networking websites has so far been provided. Third, this dissertation will attempt to deepen the knowledge of different “breeds” of YouTube users, such an objective being justified by how often– according to ICT professionals and advertisers– survey researches mix up different motivations and different user “segments”. Backing the appropriateness of such an attempt is the interest of YouTube viral advertisers in a kind of “species” of YouTube video uploaders much different from YouTube celebrities or independent creative directors. Such uploaders are usually young, tenth grade to college senior year, and act either alone or in a group of friends, enjoying the fine and intriguingly mysterious act of replicating viral videos or uploading videos to “freeze” specific intentional or unintentional episodes of their lives. Apparently just for the sake of fun. A genuine, yet well– rounded and interesting “taste” like that of the aforementioned category of users will justify renaming them throughout this work as the “sliders”, the authentic traditional American burgers. Needless to state how far this universe should be standing from those videos dissected by survey- based studies and magazines, which suggest fame-seeking, exhibitionism, self promotion as the main upload-behavior motives. Such sophisticated fame-seekers, outfitted with semi– pro tools to pursue their personal fame– strategies, will be cordially referred to as the “baguettes”, just like the exotic and hip French bread roll. When a Company like Nike launches a viral call-to-upload YouTube campaign, its actual target is a significant redemption from within the ranks of the “sliders” group. Finally, the author hopes to provide marketing practitioners with directions and recommendations for a successful strategy aimed at increasing user participation and the number of uploads in a viral video-upload campaign. The main intent of this dissertation is to uncover, research, and apply dimensions that might impact on an end user’s willingness to upload a video response on YouTube. Such dimensions span from more user-related factors, such as intents in usage and involvement in virtual communities, to more video-related variables. YouTube was preferred for the massive amount of marketing money invested in it by Companies, its worldwide pre- eminence, and because of the author’s most recent internship experience - at Google’s marketing department - where he also had the chance to collaborate on YouTube studies and strategies. The video-related dimensions, which are expected to be playing a major role in triggering video uploads, are: - The kind of video-claim, whether a genuine viral video, a video posted by a YouTube “monologuer” or a marketing campaign.
  8. 8. 6 - Individual/group– specific feature, looking for significant behavioral, motivational motivational, and experiential differences between video uploads performed whether alone or in a group of people. - The emotional attributes of the video and the task promoted therein, applying the categorizations analyzed by Gardner’s 1985 critical review, developed on much pre- existing research around mood mood-based reactions to adverts. The three behavioral dimensions reported above are amongst the most directly applicable to a campaign strategy and to its creative definition. Y they are of academic research interest Yet, as well, in that the findings could contribute to the broader theoretical viral marketing , literature, provide some orientation in understanding upload related on upload-related online consumer behavior issues, and possibly p , provide advertisers and VC administrators with new hints a and insights. Moreover, much attention will be paid to attitudes and mindsets influencing use behavior users’ on YouTube. Where possible, a theoretical framework consistent with our fo focus on the bottom impact of behavioral patterns on upload proclivity will be provided. USER GENERATED VIDEOS AND MARKETING INVESTMENTS According to data provided by independent research Company eMarketer around 22% of eMarketer, online marketing campaigns will feature a “stimulation” of User-Generated Online Video ting Generated Submissions in the near future. Another 36% of US marketers planning to bring their future. campaigns online are weighing the options and considering the effectiveness and impact of widespread, distributed brand shaping through UG videos. Percentage on total of US marketers Use Plan to start this year Would consider using 0% 5% 10% 15% 20% 25% 30% 35% 40% Would consider using Plan to start this year Use Percentage on total of US 11% 11% 36% marketers Figure 1 Call-to UG Videos in online marketing. Source eMarketer, 2008. s Fostering a User Generated Content flora means also an effort from media companies and website owners towards creating platforms, contents and community environments which could increase the weekly amount of UG videos spontaneously uploaded by viewers. The UG belief that user generated videos attract more viewers (in terms of billions of streams) than
  9. 9. 7 traditional media is strong amongst US marketers. This explains the forecasted growth of 296% of user-generated content advertising spending from 2008 to 2012. ntent US UGC advertising spending 2007 2012 2007-2012 (millions and % of online spending) 2008 (1.07%) 2010 (1.48%) 2012 (1.62%) $0 $100 $200 $300 $400 $500 $600 $700 $800 $900 US UGC advertising spending 2007 2012 (millions and % of online spending) 2007-2012 Figure 2 US Advertising Spending on UG websites. Source eMarketer, 2008. US Online Marketers' Attitudes toward UG content, 2008 (% of respondents) None of the above It will take a few years, but we will figure out a way to monetize UG content Consumers will continue to migrate towards UG content, but they will never abandon professional, … Yes, media is in big trouble and will lose dollars to UG content 0% 10% 20% 30% 40% 50% 60% 70% 80% Figure 3 US Marketers' Attitudes towards UG content. Source eMarketer, 2008.
  10. 10. 8 CONCEPTUAL FRAMEWORK CONSTRUCTS AND MEASURES UNDERLYING VIDEO UPLOAD BEHAVIOR By their very nature, digital environments originate in networks. These networks thrive on social interaction, be it specialized or broad, interpersonal or group-based, social or formal (Bagozzi, Dholakia, 2002). The focus of this research is the consumer psychology of participation (and/or its antecedents) to social networking websites (SN websites, or SNs, from now on). Therefore it is vital to recall some psychological measures to be considered and applied throughout the whole experimental data analysis phase of the dissertation. The two major research strains I will be calling on for orientation for this specific facet of the work are: Information Systems Development user behavior research (McKeen, Guimaraes & Wetherbe, 1994; Barki & Hartwick, 1994; Hartwick & Barki, 1994; Moon, 2000; Light & Wakeman, 2001; Joinson, 2001) and SN/virtual community interactive marketing literature (Herr, Kardes & Kim, 1991; Bagozzi & Dholakia, 2002; Brown, Broderick & Lee, 2007). It is immediately evident that there must be much more than simple stated intentions to being “upload friendly” in a “Broadcast Yourself©” environment. As YouTube is a website, a virtual community and a SN Information System, three measures already identified in the field of Information Systems are likely to be a good fit for a preliminary “dissection” of the conception of Video Upload Behavior into more easily employable “bricks.” Video Upload Behavior can theoretically be compared to the more or less cooperative behavior showed by participants throughout an IS pre- and post- development experiment (Barki & Hartwick, 1994). In this case, the three constructs that most visibly seem to be affecting users are: User Participation, User Involvement and User Attitude. Barki and Hartwick produced a great deal of knowledge advancement in the User Participation field. First of all, they critically reviewed the strengths and weaknesses of the previously existing literature (Olson & Ives, 1980, 1981; Baroudi et al., 1986; Franz & Robey, 1986), generating 59 items depicting specific behaviors, activities, and assignments users may be engaged with during the IS development process. Then, after carefully selecting and generating questions consistent with the User Participation, User Involvement and User Attitude conceptions shared by the authors after analyzing works by their predecessors, the authors ran several analyses on two groups of respondents in order to test, balance, refine and round out the three theoretical constructs smoothly. In generating items for the User Participation scale, a comprehensive conceptualization was employed, including direct and indirect forms of participation, formal and informal activities, activities performed alone and with others, and both general and stage–specific assignments, activities and behaviors (Barki & Hartwick, 1994). What they came up with in the end is the backbone of my definition of the following constructs. User Participation: results from a combination of: “user- IS relationship”, tapping participation activities involving a relationship between the users and the IS staff, for example “IS development processing staff kept me informed,”
  11. 11. 9 “responsibility” for a specific step in the development process, and “hands-on activities”, like hands– on systems development activities that users personally perform. User Involvement: mainly composed of two subscales: “importance” and “personal relevance”. User Attitude: which scale is given by four dyadic sets: “useful/uselessness” “good/bad” “worthless/valuable” “terrible/terrific” Much has been written regarding the likeliness of User Involvement and User Attitude as either two separate items or just the same (Fishbein & Ajzen, 1975; Osgood, et al., 1957; Thurstone, 1931; Zanna & Rempel, 1988), Barki and Hartwick (1994), found that “thoughts concerning a system in use are more differentiated than for a system to be developed in the future.” While distinct, they believed User Participation and User Involvement to be related. Reporting from their article: Users who participate in the systems development process are likely to develop beliefs that a new system is good, important, and personally relevant (…)user participation leads to positive user attitudes concerning systems being developed. Through their participation, users may be able to better communicate their information needs, which, if satisfied, will result in a better system, at least from their point of view. Because of their participation, users may perceive that they have had substantial influence on the development process and thereby develop feelings of ownership. However, participation is likely to be but one of many antecedents of involvement and attitude. Other influences include such factors as personality (e.g. need for achievement, locus of control and dominance) and experience with information systems (e.g. education, type of systems used in the past, and amount and quality of experience with other systems). The relationship between User Participation and both Involvement and Attitude is expected to be moderate in magnitude. User Participation is also proven to be one of three independent variables (McKeen, Guimaraes and Wetherbe, 1994) influencing User Satisfaction, a key construct to assess the likeliness of users participating in upload or website community activities. The relationship between User Participation and User Satisfaction is moderated by task complexity and System Complexity, while the remaining two independent variables happen to be User Influence and User- Developer communication. A deeper understanding of users’ willingness to participate in a website interaction requires another construct, forged by two of the most– quoted consumer behavior researchers in interactive marketing (Dholakia & Bagozzi, 2002). According to such literature, member participation to an active virtual community undertaking can be defined as “intentional social action,” with both individual and social characteristics we will just be beckoning at right now, postponing a bulkier explanation to the next sections.
  12. 12. 10 The individual characteristics of a member’s willingness to participate consist of constructs such as attitudes, perceived behavioral control, desires and anticipated emotions, while the social characteristics (i.e. the unique influence exerted by the community on the member) are defined by dimensions like compliance, identification and social identity. Applying the theoretical user behavior framework coming from IS literature (Barki & Hartwick, 1994; McKeen, Guimaraes and Wetherbe, 1994) and interactive marketing (Dholakia and Bagozzi, 2002) to a complex, pervasive and multitask UGC website environment like YouTube might either confirm or dismiss an approach hypothesis stating that UGC websites - and SN websites in general - can partially be explained, tested, and studied also by aid of previous research nurtured in fields contiguous to the core subject. Therefore, studying UGC- SN consumer behavior might not result in having to approach a radically pristine research area, all related consequences being known. Finally– a curious note– the relations and the disclaimers regarding User Involvement and User Participation presented by Hartwick and Barki appear to be a good answer line to the paradoxical pattern of success of YouTube & siblings. According to several survey-based studies, a percentage around 8 of all YouTube registered users actually upload videos to the website. Knowing that the users’ favorite category is user generated videos by large, that might alert Googlers and Advertisers, suggesting there might be some serious problem with User Participation, especially in “slow” Western Countries like Italy, where percentages fall dramatically. However, a striking percentage of 27 sends a video link to others, while a percentage of 23 rates videos. User Involvement, therefore, should be high and what could explain much of YouTube’s “social” success and pre-eminence, despite of a low1 rate of User Participation. ON SOCIAL NETWORKS AND VIRTUAL COMMUNITIES The assumption that YouTube is an online social network could work fine for survey-based quantitative studies, such an assumption coming out as useful especially when running competitive analyses. However, some research on the topic turned out to be necessary for a consumer/user behavior project. First of all, it appears that YouTube might be serving as a social network or a community (Goodings, Locke & Brown, 2007) only when users perceive it in such a way. Motivations, actions performed, and objectives featuring a user’s activity online can dramatically impact her own perception of the virtual platform employed, shifting the whole set of thoughts evoked from a “website-as-they” to a “website-as-it” approach (Light & Wakeman, 2001). A deeper explanation of the related findings will be provided later on in this section. 1 Generally speaking, in fact 8% is a high percentage compared to many other similar online platforms
  13. 13. 11 A definition of Virtual Community The concepts of social network and virtual community have been found to be intertwined (Goodings, Locke & Brown, 2007) through the construct of “virtual togetherness” (as in Bakardjieva, 2003), referring to the “sense of belonging that members feel even in the absence of regular contact with large groups of fellow members.” Earlier Psychology research on communities shaped a definition of community far more useful for our work than the traditional sociological/objectivist indications. A subjectivist perspective, already employed successfully in an analysis of user interactions within MySpace, emphasizes interconnectedness as a subjective property of social ties, with a “sense” of interconnection bounded by a shared experience of a given geographical location, a common “place” (see Goodings, Locke & Brown, 2007, on Sarason, 1974). This allowed researchers to understand that MySpace users may feel membership and shared emotional connection without necessarily possessing “strong ties” to large numbers of users. Finding out whether there is a sense of shared “place” – or an anchor such as– for YouTube users will be therefore a priority when analyzing their experiences. More specifically, even replicating viral videos might turn out to perform a role in shaping identities within the virtual community, given that “claims that one’s identity is grounded in a particular place can be treated as a symbolic resources that are mobilized version of identity is rendered operant” (Goodings, Locke & Brown, 2007). A collective that can lay claim to place, and finds in its relationship to such social space the basis for both a sense of its own collective history, and the grounds for a series of identities can thus be defined as a Virtual Community (Goodings, Locke & Brown, 2007). Even better is Rheingold’s 1993 definition of virtual community: “social aggregations that emerge from the Net when enough people carry on those public discussions long enough, with sufficient human feeling, to form webs of personal relationships in cyberspace.” In contrast with the many Social Network Analyses which– by advocating the use of more objectivist approaches– stressed on the importance of “size” (enough people) to support the relevance of the SN analyzed, we will be paying much attention to the second term: sufficient human feeling. Therefore, to act as if involved in a VC, a user must be part of a stream of social “anchors” (the concept of “place”), connections, and enough information material coming from self- disclosure. Given the diversity and variety of user experiences on a website, Research nurtured in the HCI field supports the hypothesis that the perception of a website as a “they” (thus a VC in the case of YouTube) or as an “it” depends largely also on the single user’s perception of the social interactions going on within the website’s “premises”. Indeed, users go about their business on websites with two levels of awareness: that of the interface and, as they get more involved in entering/sharing information, that of the social context beyond the interface. This is mainly due to the fact that, when interacting with a website, users start to
  14. 14. 12 perceive their behavior in terms of person-to-person, rather than person-to-machine relationships (Joinson, 2001; Light & Wakeman, 2001; Goodings, Locke & Brown, 2007). If the amount of online self-disclosure allowed by users is crucial for a proactive, interactive and content-generating experience, it will be necessary to measure the magnitude of the impact performed by the three video– related variables on such willingness to self– disclose. It goes unsaid that a user’s upload proclivity might vary based on whether she experiences YouTube as a mere repository of entertaining video material or as a unique community with a certain specific shared “sense of place.” Most luckily, earlier research on self-disclosure through PC or virtual interfaces has shown to be extremely inspirational and coherent with our research objectives (Lawler & Yoon, 1998; Moon, 2000; Joinson, 2001; Bagozzi & Dholakia, 2002; Eguíluz, Zimmermann, Cela-Conde & San Miguel, 2005, Dobele, Lindgreen, Beverland, Vanhamme & van Wijk, 2007). YouTube as Social Network The main question at this point is: when perceived as a “living” website, as a “they”, what kind of SN is YouTube? A recently published sound and inspirational conceptual analysis of online social networks by Brown, Broderick and Lee (2007) came to results consistent with the theoretical lenses of our research.Reporting from their work: “Web sites are perceived by Web users as actors in their own right in online social networks. Specifically, in the online context, individuals seemed to more commonly interact with Web sites and information, rather that with actual individuals”. A description given of an online social network is similar to some sort of “knowledge co-op”. Actors taking part on an online SN mainly relate to the website and only occasionally do they engage in individual-to-individual contact. What counts is that collectively each individual contributes to and receives information from the online community, so that the latter becomes the primary unit of relationship rather than the individual (Brown, Broderick & Lee, 2007). The– hopefully– mutual information exchange happens therefore between a “community” and the individual. Figure 4 Online strong one-to-many social network (Brown, Broderick & Lee, 2007) Figure 4 displays the functioning of a one-to-many social network just like YouTube, where it is up to the community to feed the user with content and up to the user to “return the
  15. 15. 13 favor,” so that the usefulness of the website and the credibility of its content is nurtured and keeps growing in the best direction possible. User– to– user communication is always possible, yet not frequently or regularly employed. Clearly, there are many social networks out there, and although the aforementioned conceptualization of them sounds consistent to YouTube, it definitely appears out of place when thinking about, for instance, a social network like Facebook. Figure 5 clarifies these discrepancies. YouTube YouTube eBay 3rd party One 2 many Viral vids/ YT content celebs collection Facebook Linkedin Many 2 many WAYN Personal Functional Figure 5 Author's elaboration on Brown, Broderick & Lee (2007) Figure 5 is an author’s elaboration on Brown, Broderick & Lee (2007) and features some of the most renowned online social networks as instances (thus it does in no way aim at analyzing the whole online social networks universe). Online social networks can be broken down into four combinations of two main dimensions: - Whether its structure fosters a one-to-many interaction scheme between users or a direct user-to-user communication structure. - Whether the website is employed more for “functional” or “personal” relationships, where in the former concept, all purely informational needs are corralling, and the latter happens whenever some sort of “committed partnership” (Brown, Broderick & Lee, 2007), or “flings” (short- term engagement to the website of high-emotional or resource-based reward but lacking any commitment), or the need to remain “part of a scene” or “always updated” is going on between the user and the website. With its marketing strategy, YouTube has been able to settle upon two key positions. Respecting the “one-to-many/personal” spot, that one is defended and developed by Google by means of regular strategies and lead-user reach outs aimed at finding ways to encourage bigger masses of users to upload their personal videos. Most of such actions by the Company are undertaken within a broader adaptive experimentation context, and can turn out to be very costly. Also prizes and rewards, like the yearly YouTube awards, are part of such a strategy. By watching YouTube celebrities and/or viewing- and hopefully replicating- the latest viral videos, the community- connection heats on. In the second position, the “one-to-many/functional” spot, is where YouTube has been the most controversial. Letting users upload an overwhelming mass of third-party content has
  16. 16. 14 been meaning trouble for Google itself, pushing it towards setting up a 24/7 video removal service, co-operating with the law enforcement community and giving away super-expensive “YouTube branded channels” advertising pages to media companies and content producers so that a non-belligerent balance could be found. This is also where users can end up having a “website as it” relationship with YouTube. Knowing that the website cannot count on the offer of massive third-party content to be keeping its competitive advantage, a sustainable, yet challenging, growth in the UGC (user generated content) has become a priority in order to keep the website attractive to both users and advertisers. What marketers can do with YouTube is follow the two arrows portrayed in the grid, i.e. paying so that the supremacy on the upper part of the grid can be moved “down” to the lower part of the graph, translating the strength of the connections already activated in the one-to-many scenario into a gigantic potential for tailored word of mouth-based one-to-one viral marketing. No other business model could have made a website go legal and big so quickly. Brown, Broderick & Lee (2007) also zeroed in on the relations between group homophily, site homophily, site tie strengths, and personal interests. Since one of our hypotheses is such that performing (or calling to perform) a certain activity in a group or alone can have an impact on the willingness and likeliness to upload a user generated video, their findings are to be kept in consideration as much as the literature on role differences development in social networks (Eguíluz, Zimmermann, Cela-Conde and San Miguel, 2005), group versus individual performances (Lawler & Yoon, 1998; Sparrowe, Liden, Wayne & Kraimer, 2001), social comparison (Burson, Larrick, Soll, 2005). Findings demonstrate a strong correlation between site homophily, fostered by a close match between individuals’ interests and those exhibited by the website, and the strength of the tie between the user and the online platform. The graph reported below recaps the relations unveiled. Source: Brown, Broderick & Lee, 2007 Finally, website credibility plays a pivotal role in the whole mechanism, so we can also add site branding, consistent with findings from Human-Computer Interaction research (Light & Wakeman, 2001).
  17. 17. 15 RESEARCH DESIGN AND DATA ANALYSIS This analysis is designed to rely on the insights derived from the progression of two inter- connected blocks of specifically– designed inquiries: a Qualitative round of research and a following, Quantitative stimulus–response experiment with viral videos, paired with a preliminary survey study. QUALITATIVE ANALYSIS In order to move further from the literary framework, evaluate users’ experiences and deepen the knowledge of experiential modules, thought patterns and usage-related identities in the UGC online environment, a great deal of qualitative analysis is necessary. The support provided to the field of online user experience analysis by earlier consumer behavior research- spanning from online marketing to consumer culture theory- has proven to be simply invaluable ( Barki and Hartwick, 1994; McKeen, Guimaraes and Wetherbe, 1996; Thompson, 1997; Moon, 2000; Light and Wakeman, 2001; Sparrowe, Liden, Wayne and Kraimer, 2001; Joinson, 2001; Bagozzi and Dholakia, 2002; Kozinets, 2002; Eguíluz, Zimmermann, Cela- Conde and San Miguel, 2005; Goodings, Locke and Brown, 2007; Brown, Broderick and Lee, 2007; Dobele, Lindgreen, Beverland, Vanhamme and van Wijk, 2007; Mandel and Nowlis, 2008; Kozinets, 2008). The identification of ideological identity constructs when studying technology narratives ( Goodings, Locke and Brown, 2007; Kozinets, 2008), the methodology employed in order to come to reliable assumptions on the interaction of behavioral variables based on users’ discourses (Thompson, 1997; Kozinets, 2002), and the definition of clear factor items to stress when planning a survey, are all tasks that can be more easily performed through the aid of a cross– discipline literary framework. Rather than asking participants to state how much the thought of responding to a given online video would make them feel involved, intrigued, amused, interested or motivated; this research has been designed so that emotional, utilitarian, experiential and social attributes spontaneously recalled and defined by tested subjects would then be analyzed and matched with the experiential traits that, according to participants themselves, might have featured the video upload experience of the authors of a set of viral videos displayed right after each interviewing session, asking them only at the end of each video to declare their appreciation to any extent and degree. In so doing might the biases naturally spun off by stated intentions be nullified, making it possible to come to reliable and consistent conclusions about what expectations, social structures, feelings, narratives and experiential traits marketing managers should utilize in order to make a viral video campaign as viral as possible in terms of the number of user generated video responses ignited.
  18. 18. 16 RESEARCH TOOLS The Qualitative part of the research features two personal interviews, two focus groups and two user journals of 15 days of length each. In so doing, might such a choice foster a deeper knowledge of possible distinguished consumer– related and video– related influences on upload behavior. In terms of age, subjects were all 21 to 25 years old- one of the most “active” and profitable age ranges, according to YouTube. In order to obtain content as “western” as possible (therefore limiting the preponderance of topics and insights coming from the mindsets and experiences of Italian subjects), one of the two focus groups was held with a group of exchange students coming from the US, New Zealand and the Netherlands. All of the subjects invited are familiar with YouTube, some of them also have some experience with video uploading. The Qualitative round of empirical research was focused on understanding: - The feelings, meanings and experiences recalled and connected to the broader UG/SN category - The way users operate a distinction between UG websites based on behavioral and experiential parameters - The way “blank users”2 see the world around themselves: active uploaders and the perception about the “service” they do; the situational and behavioral circumstances under which passive visitors have been or have been wanting to upload videos or user-generated content; users’ thoughts about what drives people to upload videos and ideas about how the online “fauna” looks like (i.e. how online activities communicate online identities) - Users’ perceptions about their behavior on and regarding YouTube and the behavior of others - The drivers of perceptual awareness of the social space behind and through the computer’s screen - Dimensions of expectations, sense of belonging, content ownership, rewards - Peculiar interesting consumer behavior insights coming from video upload experience recalls - The role of user involvement and participation - Significant group/team-related and task- related differences in video upload behavior Qualitative research turned out to be a great help in gaining useful insights in order to answer questions such as: - What kind of user would we be talking to in a prospective viral marketing campaign? 2 Users who have not added any information to their YouTube account. In this work, blank users will be employed to describe the vast majority of “mute” users on YouTube.
  19. 19. 17 - What matters “experientially” to such users when uploading/thinking of uploading videos on YouTube? Under what circumstances? Finally, content generated by user journals, personal interviews and focus groups has been analyzed through the lens of the selected literature, so that it would provide both a guidance in deepening the actual survey items, and a deeper knowledge of the three variables researched. Additionally, a set of viral videos and viral video responses had been progressively built up through a try-and-see approach which aimed at involving participants in selecting, discussing and analyzing videos. After gaining insights throughout the two personal interviews on the possible main forces interacting behind a user’s final decision to upload a video, a comparison with earlier literature helped in better defining the expectations on the outcome of a subsequent experiment. Four fields of variables are, to an unknown extent, supposed to be exerting some influence on the end user’s upload proclivity. Consistent with the statements of all interviewees, the act of uploading a video can in equal measure be either impulsive or a planned activity. Keeping this “equation” in mind might help campaign planners define clearly the kind of stimulus to be conveyed through a call-to- upload video. The four variables are: - Social implications: performing- or planning to perform- a video upload is a veritable social act: friends will see it, “our face” is right out there for the world to see, people will be watching and commenting, etc… In a few words, proactive participation on YouTube is an emotionally- connecting act, consistent with findings about viral messages in recently published literature (Dobele, LIndgreen, Vanhamme & van Wijk; 2007). According to the interviewees, what appears to be the main discriminating “social” factor impacting the wish to upload a video is whether the video-call is performed by a single actor or by a group of people and also if it calls for a collective or an individual response. - Mood: Just like in Advertising (Bakamitsos, 2006), mood is supposed to play a predominant role also along the psychological path leading to a video upload. Participants to the qualitative sessions have stressed the importance of three elements: • The mood induced in the viewer by the video • The mood of the performers of the video as perceived by the audience, functioning therefore as a cue in the prediction about the enjoyment of the prospective experience of filming and posting a video response • The coherence of the two above-mentioned elements with the user’s own emotional motives (e.g. “this looks like a very fun video to make” vs. “…but I want my video to be meaningful and intense”). - Topic: Usual/Unusual topics seem to attract and activate end users in different measures. Unusual topics certainly raise a lot of curiosity, while more general topics appeal to a much broader audience, though in different measures depending on each user’s personal interests and tastes.
  20. 20. 18 - Context: Upload proclivity might also be significantly session– dependent, according to various different statements collected throughout both personal interviews and focus groups. Also (Bakamitsos, 2006), a relevant context, if associated with a positive mood, should foster a more positive evaluation of the product/action proposed. As an example, a session featuring mostly soccer-related videos and searches might be more effective in causing a video response in the soccer video category. If this were true, a continuous effort to enhance the quality of the targeting of “related videos” appears to be almost mandatory in order to keep the upload rate as high as possible. The four variables had emerged throughout the personal interviews and they got reinforced by empirical experience confirmed by various industry experts from advertisers to campaign strategists and marketers, both at Google and within its clients. This also served as a guidance in setting up the structure of later focus groups. As anticipated earlier, in order to gain a better insight on the patterns of influence, two research tools have been specifically employed: a video “bouquet” and User Journals. Video “bouquet” The first 3 variables can be better understood by inviting participants to express opinions and rate a carefully selected set of YouTube viral videos and video responses. In order to keep the risk of biases low, participants are not asked whether they would engage in acts similar to those featured in the video selection, rather they are asked to describe the kind of experience they guess the participants of the featured videos might have lived, and to express the decree to which such an experience matches with their previously “emotional” preferences. Throughout the Quantitative survey + experiment research, participants might be asked, after expressing qualitative opinions about the videos viewed, to rate their “spot” willingness to upload a video response and then to rate on a scale how much every one of a set of influencing items makes them feel like video-responding. While “Social implications” and “Topic” are to be controlled variables, “Mood” will be left to the participants, in order to gain further insight on what ways such variable influences viewers’ upload proclivity. VIDEO BOUQUET SELECTION CRITERIA After the two personal interviews, in which considerable time had been dedicated to gaining insights about the main discriminating factors influencing users’ interest in uploading a viral video response, a set of 19 viral videos has been created, trying to cover all possible combinations. These 19 videos come from a bigger set of 40 clips collected through suggestions and interaction with subjects during both personal interviews and focus groups. In this case, qualitative researched served as an inspiration and as an orientation for the final content of the video “bouquet”. The whole set of videos is then divided into 8 “clusters” with different characteristics. Each cluster features one viral video call and one or more responses to it (see Appendix). Viral video: in order to fit in, a viral video needs to have received a sufficiently significant (60 or more) number of posted replies and at least 10 video responses, including “replications”- mere viral video response/ linked responses (responses not directly linked to the main video
  21. 21. 19 but featuring a “Re: viral video title” title)- and interpretations, i.e. modifications of the task proposed in the main video, yet linked to it. A video call will be labeled either as “Viral Video”- a video not explicitly intended to become viral- or a “Viral Call”, namely a video who wants to become viral and invites others to replicate/respond. Topic: Topics can be labeled as “general”, like depictions of ordinary situations (such as sports fans filming themselves while spurring their home team), or “unusual” (e.g. the Coke + Mentos experiment). In order to avoid subjectivity, a usual/unusual scale previously developed by Goldberg and Gorn (1987) has been orally tested on all interviewees when showing the videos during personal interviews and focus groups. Alternatively, in case of marketing viral videos- “Branded Campaigns”- they can either be labeled as “Soft Branding”- where the logo and the commercial intent of the video are hidden or non-priority- or “Heavy Branding”, with the brand, product or logo being clearly shown and playing a leading role. These last two parameters have been tested by asking participants: “Do you perceive there is a brand or a commercial intent behind this video or not?” Social Implications: Labeled as “Individual Action”, which is when the task is performed by a single person or a single person with an aide, or “Group Action.” Combining the labels above, the set of videos has been defined and tested on the participants to the focus group by making them watch some of the videos listed in the Appendix. User Journals In order to gain some insights on the dynamics featuring a possible session-dependency of viral response upload proclivity, following users along their daily usage of YouTube has become necessary. Two males, age 22-24, both previously involved in focus groups and showing different attitudes towards a proactive use of web 2.0 technologies and towards technology in general, have been invited to keep a diary for 15 days following strict assignments. The two subjects who were invited to write a user experience diary, with a focus on potential browsing session-related dynamics impacting on their own perceived eagerness to upload a video, are both males, age 22 to 24, Italian Nationals and pretty far apart from each other in terms of consumption mindsets when it comes to YouTube, as they demonstrated throughout a previously run focus group. The thoughts and feelings expressed at the time by the two subjects have been taken as a hint of them possibly providing even deeper insights into the “segments” they might belong to. See the Appendix for scripts, user journal forms/assignments and a list of the videos shown to participants. Using Kozinets’ (2008) categorization of technology ideologies, and having supposedly placed the four3 nodes of the semiotic square in a row, Gaetano, 22, appeared to be closer 3 Kozinets (2008) provides us with 4 ideological nodes and identities: Green Luddite (opposes technology firmly), Work Machine (welcomes technology as a reliable aid in achieving a better personal productivity),
  22. 22. 20 to (yet, unlike Bianca, not entirely part of) a “work machine” ideological mindset, which might justify his need- made explicit during an earlier focus group session- for a team, a clearly identified recipient, a goal to reach and a target audience, when uploading a video. Roberto, 24, has often shown understanding and curiosity towards typically “techspressive” features of YouTube behavior (though not being completely techspressive just like Brett or Fabio). Conversations entertained with industry experts, and articles published in major US magazines and blogs, suggest that it is in that grey area in between “work machine” and “techspressive” that the best target audiences and consumer insights for viral video campaigns are lurking. KEY FINDINGS FROM INTERVIEWS AND FOCUS GROUPS A content analysis was run taking inspiration from the methodology and the examples provided by some of the articles making up the designed literary framework (Thompson, 1997; Moon, 2000; Light and Wakeman, 2001; Sparrowe, Liden, Wayne and Kraimer, 2001; Bagozzi and Dholakia, 2002; Kozinets, 2002; Goodings, Locke and Brown, 2007; Dobele, Lindgreen, Beverland, Vanhamme and van Wijk, 2007; Kozinets, 2008). Almost all participants to the qualitative sessions were at the same time confident with using YouTube, and not used to thinking too much about what matters to them in such virtual social environment. This specific feature has made talking about participation on YouTube an almost unprecedented topic for the subjects interviewed. Furthermore, earlier academic research has not yet provided consumer behavior analysts with universally valid a priori measures to code for when analyzing transcripts. Therefore, an a posteriori/relational analysis focus has been preferred. This was so that it would have been possible to go beyond mere word presence or repetition, exploring the relationships between the concepts identified as the analysis went on. The approach followed is in line with the meaning condensation approach followed in coding by Brown, Broderick and Lee (2007). First of all, time counts have been taken of all the instances in which interviewees discussed or recalled a specific topic/concept. This implied reading, aggregating and analyzing transcripts content more than three times per construct. As an example, to justify a thorough analytical attention, a specific topic needed to “last” at least 15/20 minutes on a 90 minute interview. Then, once all the transcript fractions referring to a topic had been identified and isolated, the analysis relied on a traditional coding for repetition of words and synonyms (coding for frequency) with an aggressive level of generalization. Coding nodes based on theme has therefore been of great help in determining the allocation of time counts to concepts. Although some constructs such as Homophily or Tie Strength were supposed to somehow get progressively brought up by participants throughout the conversations, such constructs were not used as strict preliminary structuring devices, due to the novelty of the subject for all the interviewees and because using strict parameters for a scarcely investigated topic such as Video Upload might Techspressive (welcomes technology as a means of self-expression) and Techtopian (technology consumption as social progess).
  23. 23. 21 have pre-empted new subjects, topics, constructs or variables from emerging. It was better to see what the participants would say and then look for similarities in the constructs previously developed by literature and already identified during the theoretical frame– working part of this dissertation. Finally, where possible, graphical mapping of elicited concepts was performed, providing results such as the ones featured on Table 1. Again, the combined usage of tools typical of both conceptual analysis (e.g. word counts and time counts) and of relational analysis (e.g. graphical mapping and coding for theme) makes my approach a hybrid kind of one, in line with the approach taken by Brown, Broderick and Lee (2007). Quantitative Analysis Software QSRNVIVO 8 (Service Pack 2) has been used to run sound and reliable in- node Word Queries on analyzed transcripts. The results of such queries for each coding node discussed in this paper are to be found in the Appendix. Based on content elicited through both Personal Interviews and Focus Groups, three major concepts pivotal in understanding the forces influencing the subjects’ upload experience perception and proclivity have been isolated and defined. Such concepts are: - The experiential usage of the UG website, with implications regarding the perception of the website as an “it” or as a “they” (the importance of such a dimension having been already foreseen by Joinson, 2001; Light & Wakeman, 2001; Goodings, Locke & Brown, 2007) - The user’s Web 2.0 identity construct and the related personal perception of the payoff of a prospective video upload act - The narrative structure of the upload initiative and of the video itself Describing such areas would contribute to a more thorough definition of the items composing the three research variables explained in the previous paragraph, in order to test them out on a larger- scale through a survey. Experiential Usage of the UG Website Early in the talking during focus groups and interviews had it become more and more clear that users’ perceptions about the meaning and meaningfulness of a prospective upload to a UG website are closely related to the idea they have of their own “download” experience across the website itself. What appears to be orienting users experiential perceptions across such a scenario could be fairly illustrated by the “UGC Experience Clusters map” reported below, a map specifically constructed by the author from original verbal content elicited throughout Focus Groups, following the methodology employed by Brown, Broderick and Lee (2007). Interaction between participants of the Focus Groups has made them come to agree on a general conceptual framing for user generated web entities and the usefulness users benefit from by taking a free tour on them or even registering to them.
  24. 24. 22 The numbers summarize the importance and appreciation (1= highest, 4= lowest) participants gave to the areas portrayed. Content Appeal Limited Broad MySpace Empowering Bebo 1 Blogs 2 Reality Facebook Technorati Netlog YouTube YouTube Service Virtualness Enriching Chatroom Second Life V.C.'s 3 4 Table 1 Author's elaboration on interview data Such ranking has been made possible by comparing the adjectives, adverbs and nouns employed by the interviewees when talking about the subject. It became necessary to make sure that participants would not incur in judgment distortions about content relevance to a general audience by confusing the issue with personal relevance. In order to do so, participants were specifically asked to generalize about variables and discriminant factors. Content reliability was repeatedly brought up as an important factor throughout the discussions, and showed to play a pivotal role in defining users’ download and upload experiential sets. The reliability dimension, depicted as an arrow bridging across the upper part of the map, appears to be a either/or variable, where the content featured on the website spans, as already mentioned, from “easy to verify and correct” to “hard to verify and correct”. The availability and accessibility of third party content editing tools (such as the ones provided by Wikipedia) and the perceived size of the audience interested in checking on a specific piece of information are the main variables underneath such perception. Furthermore, content reliability seems to be significantly related to the user’s perception of the website as a “it” or as a “they” following the dynamics illustrated by Joinson (2001); Light & Wakeman (2001); Goodings, Locke & Brown (2007); yet perhaps (for a more detailed description please refer to the following sections) with inverted significance4. Content Appeal: Interviewees have spontaneously acknowledged that one of the main discriminant factors of their own perception of a UG website experience is the website’s 4 See Quantitative Analysis, Usage- related variables.
  25. 25. 23 content. Different content implies different interests in using the website, and different interests mean different attitudes or even mindsets taking place within the website’s premises. Traditional indicators of a website’s stickiness5, such as Total Page Views, Total Pages per User or the Average Time Spent on the website (all available through Nielsen Netratings), are clearly not enough to explain how sticky (and therefore potentially profitable) a website experience is. Facebook and YouTube are arguably among the stickiest websites on Earth, yet the perceived browsing experiences are far apart from each other. Moreover, “content appeal” is not necessarily related to the very subject of the UG information hosted on the platform. According to the interviewed users, it does not really matter if the website is about recipes or first aid, tornado alerts or politics, showgirls or microbreweries. Indeed, curiosity is perceived as one of the main drivers of online traffic growth in the UG scenario: users are attracted and encouraged to share content by new topics, ideas and concepts- especially people 18 to 35 years old (OECD, 2007)- and are well aware of the impact some UG websites can have on their own cultural mindsets. Tommaso, 24, Italy: Besides being extremely useful to the “management” of my daily social life, the Facebook is awesome because, just like many others out there, it has brought to our (Italian) culture an element, a tool, which was typical of a different culture, the US one, like the Yearbook. This is some huge thing when you think about it… What “content appeal” is thus all about: - The perceived size of the audience that could possibly be interested in (and have access to) the information featured online. - The kind of audience the uploaded information is perceived to be mostly targeted to (like a clique of friends for Facebook or the whole of mankind for Wikipedia). - The kind of interest the website is perceived to generate: particular, like a website offering specific information about a specified topic, or broad and generalized, like an encyclopedic website. Service: The perceived meaning of a personally uploaded piece of information significantly varies in the mind of the user based on the kind of service the online platform (and the specific upload) does to the user herself. Namely, if the website is perceived as a service itself, i.e. as a set of instruments functional to the satisfaction of needs that pertain to real life (like keeping in touch with people we personally know in a more efficient way), the user should find herself less inhibited in uploading personal content than she would be, were she positioned in a different sector of the map. This is the “reality empowering” perception of the offer of a UG website. The “virtualness enriching” is the complete opposite: to a rich (in terms of multimedia and information content) virtual environment- like Second Life- user generated features are 5 Stickiness is to be intended as the degree to which a specific online platform is apt to regularly engage its visitors in long usage sessions.
  26. 26. 24 added or allowed, in an attempt to increase social connectivity. It could be explained through the catchphrase “meeting friends online vs. meeting online friends.” According to the interviewees, a combination of a “reality empowering” perception of the website’s purpose and a “limited” content appeal would be the most upload- encouraging match for most of people. If this was proven correct, the theory provided by Light and Wakeman (2001) on the two levels of perception of a website- as an “it”(interface) and as a “they” (social interaction behind)- could be enriched with insights about the level of user engagement partially resulting from the perception of the website. In fact, so far have our findings suggested that when the website is perceived as a “it”, i.e. as a service, a tool, more than as an active community, the audience’s upload proclivity should be higher than in the case of the website as a “they”, i.e. a clearly perceived self-sustaining living community. Apparently, this might look a little tricky. The fact is, interviewees have in fact someway redefined the definition of the website as an “it”, from a simple tool to a device that allows one to share what she wants and with whom she wants, without having to inevitably deal with a broader, unknown and overly variegated community. Bianca, 25, Italy: With Wikipedia you know that if you don’t go correcting a statement someone else sooner or later will be doing it anyways. With Facebook it’s, like… enclosed, and it’s all about who you know that is behind the screen, the friends you are connected with. I feel my contribution is valuable, like… I’m motivated in “bringing” something if I can collaborate with a defined group of people. In the case of online, I guess this would mean that the website means something to me if it is functional to what I have to get done… Many other similar statements have come from most of the tested subjects. It looks like more than as a mere “it”, then, the UG platform is perceived as a “we”: a “it” set of tools purposely designed for a group collaboration. If this is appropriate for most of the interviewees, it has been suggested by participants that its influence changes depending on the single user’s identity construct. The real difference might be, as suggested by Brett, 22, and Alberto, 24, in what one is looking for when uploading some content. Brett, 22, NY: If you look at YouTube as a thing, a service, that is strictly functional to what you need to do in real life, like showing a video of yours to friends, that’s one thing. You get a benefit out of it, a service. If instead you are like those Good Samaritans that do uploads for some sort of common good of humanity, or a Hannah Montana ( continuing a comment from Kelly, 21) fan who rips videos and uploads them all day because he wants his favorite singer to live on in history, or a dancer or singer wanting to show his talent to the world, it’s different. It’s like you’re looking for something less solid, it’s more of a hope and a pleasure than a service… Alberto, 24, Italy: It depends on what kind of YouTube user you are, how you use and see such technologies… The “UGC Experience Clusters map” was derived from the content of the interaction between the participants throughout the qualitative research initiatives, and it requires a major specification about its salience in a broader context of a general classification of different upload attitudes and behaviors.
  27. 27. 25 First of all, it appears to serve best as a dynamic, moment– by– moment compass and should therefore not be taken as a static, all– encompassing model. Users have repeatedly specified how task-related their upload and download perception of the website is. Such a strong dependence on the contingency of the use of the online platform has been, however, smoothed by the eminent and more “static” role played by “technological identities”, according to the subjects interviewed. As an example, Gaetano, 22, stated that uploading content is sometimes felt as a contribution “owed” to earlier uploaders, whereas it feels like “such people should get paid back.” The unique positioning of the single user on a spot in the UGC experience map seems to not be enough to make reasonable predictions on the likeliness of such a “payback” mechanism to take place. Participants have agreed that what we can name “web 2.0. identity constructs” might actually be a veritable clincher in the decisive moment when a user opts for engaging in uploading original content or not. Technological identity constructs seem to be molding upload behaviors in a manner similar to the technology ideologies recently researched by Kozinets (2008). A semiotic square analysis of the subject is thus explained in the following paragraphs. Personal perception of a video– upload activity’s payoff and Web 2.0 identity constructs “What am I getting out of this?”, “What’s in it for me?.” Both passive, “blank account” users, who have never gotten “activated” by performing video-response acts over YouTube, and active youtubers happen to ask themselves similar questions before deciding whether to upload a video or not. Almost all successful viral-video marketing campaigns have, deep underneath their appearance, a clear definition of the kind of “reward” consumers should know they would be getting “in return” for their effort in uploading a video. As an example, in a hypothetical situation in which user “A” expects uploading a video of him and his brother passing the pigskin to be “nothing more than fun,” then the experiential payoff of the upload decided by upload decided by NFL Superbowl marketers should be consistent with that statement. Throughout the qualitative research sessions, participants linked their depictions of the “identity types” of YouTube users (description of the fauna) to the “payoff” people get from uploading videos. In more edible words, what you would or would not go for depends on who you are. Kelly, 21, MN: I’m sure that those guys who post videos like everything from Hannah Montana just want the world to know how great (they think) she is, they are such huge fans of hers, and I am sure they are always on it (YouTube) to see how many people comment their videos. Brittany, 21, AZ: Yes, they must be spending all day there, ripping videos to “spread the word” and for sure they are happy they are doing it.
  28. 28. 26 Gaetano, 22, Italy: Sometimes when I go watch old goals scored by old soccer glories, or old episodes of forgotten TV shows, the first thing I think is that I am thankful to those who somehow God only knows have found, ripped and posted that stuff. But then I think, they must love these videos as much as I do, so would I do the same they have done had I found the same videos at home in, I don’t know, videotape? Most probably, because if you like something a lot you want it to stay like that forever through time, and I think YouTube allows you to do so: freeze time for the things you like most. Kelly, 21, MN: As for me, I’m really not that technological. Yes, I have the Facebook which I use pretty (laughs) intensively (others laugh), and at school I do everything on the computer but the only way I see uploading videos on YouTube as interesting is when you want to show someone what you are doing or how you are doing, especially if it’s something funny. For instance, we (referring to other people in the room) made a video to show my mom who my friends are down here (exchanging in Italy), so she went seeing it on YouTube and told me, and then I was happy I could share. Brett, 22, NY: I’m pretty much always on YouTube, I’m pretty active. A lot of times I find myself commenting other people’s accounts or videos both for sharing but also because I want them to check out my own account and leave some feedback about my songs (Brett is pursuing a music career as a singer and composer). The extracts reported suggest that the kind of use of technology and the identity traits of every single user merge whereas technology bears an evident social significance. This contributes to turning a set of habits, routines and beliefs related to the users’ very own vision of the whole Internet-thing into four well-defined Web 2.0 identity constructs, as developed by participants as the conversations went on. Furthermore, later on in this section we will see how the technology identity/pursued upload payoff matching would appear as an unsolvable “dichotomy”(Kozinets 2008) if looked through under a static-model lens. In order to get to an understanding of how technology identities impact on the relevance of a proposed upload payoff for the end user , it might be good to start with an application of Kozinets’ (2008) semiotic square of the technology ideologies to the contents of the qualitative sessions. Moving beyond paradoxes: an introduction to the semiotic square Throughout the sessions, the participants’ own “technology identities” (or mindsets) have been brought up in ways suggesting a consistency between our research focus and that of Kozinets’ work of semiotic analysis. Reporting Kozinets, 2008: Many studies dichotomize technology ideology, implying that consumers who adopt these ideologies fall into particular categories of either resistant technophobes or exuberant technophiles(…). Alternately, a “paradoxical” viewpoint of technology suggests a more complex viewpoint in which consumers can simultaneously straddle opposing ideologies(…).
  29. 29. 27 The semiotic square is in wide use in cultural studies and it was developed in the late 80’s as a way to analyze paired concepts. It maps the logical conjunctions and disjunctions that relate the key semantic figures of a text through their polarities (Kozinets 2008). The semiotic square’s ability to penetrate and enrich apparent binary oppositions is particularly valuable in a study of technology ideology. I decided to use the semiotic square for many different reasons. The first reason is that it has been successfully applied by Kozinets to a subject like online identities, behavioral motives and beliefs, which has always been extremely complex to frame in a model. It would still be impossible to explain through a simple survey-based factor analysis how certain users who fit well in a category according to their questionnaire responses end up acting in contrast with their allocation often and unpredictably. A concept like the ideological element, with an analysis of its nodal point, concepts and interpellations, can provide marketers with a better and more efficient orientation when it comes to finding new ways to activate users through viral video campaigns. Through an analysis of users’ discourses, concepts, meanings, valences and main beliefs are positioned in a “web” of interrelations. The whole set is then defined as an “ideological element”, one of the four elements which, when positioned at any angle of the square, represents the extremes of the whole field of consumers’ ideologies about technology. For instance, knowing what contradictory signifiers usually feature the ideology behind the behavior of some of our users might accurately tell us what kind of creative direction to give or not to give to our marketing campaign. Figure 6 structure of an ideological element as in Kozinets (2008)
  30. 30. 28 A further reason why the semiotic square has turned out to be a useful tool for the analysis of statements regarding technological “identities” in web 2.0 environments is its peculiarity as a methodology. Indeed, it is set up to take into consideration both the results of strictly qualitative research (like interpretive analysis of consumer data) and any technology-related and mass-cultural text the researcher decides to trust and reap information from. This is very useful for a field like web 2.0 and YouTube, where knowledge about its inner dynamics is often tacit and developed through the sharing of information and opinions among industry experts. Finally, experiences and opinions shared by the participants invited to the interview sessions seem to almost naturally match with the statements reported on Kozinets’(2008) research on the mechanisms that make users move from an ideological coordinate to another. First, I will attempt to give a reading on some of the content gleaned throughout the interviews regarding the role of beliefs and identity in the usage of YouTube’s video upload functions. Kozinets’ semiotic map will be the canvas, and the nodal points will not be modified. Then, I will propose four new identity mindsets to be tested in a later quantitative study, based on what had emerged throughout the Focus Group sessions. Limits of this analysis and insights on possible further developments of research on the role of web 2.0 identity constructs through the aid of the semiotic square will be discussed, as well. In the semiotic square much attention is given to experiences recalled by the participants which suggest that the shifts (black arrows) already examined by Kozinets actually take place with the use of social technologies. A major limitation of my analysis is that no participant is placed on a single ideological element. This is because the structure of the focus groups did not heavily stress how users perceive and define their own behaviors but on how they experience changes in it, moments in which they do something thus far unexpected (like deciding to upload a video, which doesn’t happen often for around 92% of YouTube users, source YouTube) and how they build expectations on the behavior of others based on the relevant manifestations of their usage of the website. Therefore, it was not part of the intentions translated into the qualitative research design to get enough data to tuck single participants into the semiotic square, which would have probably required an additional research, with a purposely structured set of Focus Groups cutting off all aspects that are not directly related to “nodal positioning” of participants. What this analysis really is about is endowing the further steps of research with elements pertaining to behavioral areas on which survey respondents can be tested and measured. Every internet user has in herself elements of all the nodal points. However, what makes a difference is the combination of them and the shifts users make from one ideological mindset to another depending on the actions to be performed. Before reporting excerpts of the Focus Group interviews, a brief overview of Kozinets’ four ideological points is needed. Techtopian Ideology: The technologically utopian ideology is articulated around the idea that technological progress is the necessary condition of social progress. It is a very appealing ideology and many users find themselves agreeing with some or all of its assumptions.
  31. 31. 29 Although the techtopian ideological pattern implies that some kind of technological sublime can not only render observers speechless but can also take Mankind to a implicitly good “higher level” of development. Contradictions arise from the placement of an overtly moral tone and optimistic perspective over technology’s essential amorality and pragmatic inaccessibility (Kozinets 2008). The Green Luddite Ideology: With the advent of the Industrial Revolution, the Luddite movement, organized in ranks like an anti-industrial militia, regularly engaged in destroying textile mills. Derivations of the beliefs of the movement still raise the interest of the media, like the antiglobalizers, the hippies, etc. Over time, the anti-industry aspects of the Green Luddite ideology became increasingly irrelevant to the average consumer, with the most current, pertinent, and widespread articulation focusing on the supreme good of nature, traditional ways of life and environmental- and authenticity- driven values. The Techtopian and the Green Luddite ideologies are centrally opposed in the ideological field. It’s a conflict of morality, even if internal contradictions mollify such a stark opposition (Kozinets 2008). The Work Machine Ideology: The nodal point of the Work Machine ideology articulates meanings of industriousness, efficiency, and personal empowerment onto technology, elevating it into an engine of national, global, industrial, corporate, and individual worker Figure 7 The semiotic square representing the ideological field of technology in its totality, as in Kozinets (2008)
  32. 32. 30 wealth and success. The Work Machine ideology articulates technology onto collaboration, productivity, efficiency. The Green Luddite and Work Machine ideologies are in contrast based on a contrariety of standards: considered using the Green Luddite Humanist values, technology is detrimental, while through the pragmatic Work Machine’s productive standards of achievement, technology is beneficial (Kozinets 2008). The Techspressive Ideology: This is the most recently developed element of the ideological field. Ever since the first interactive video games, the Techspressive ideology has meant that some supreme fulfillment of pleasure is to be articulated onto the category of technology. Articulations of self– expression, youth, creativity and fashion form the heart of this ideology (Kozinets 2008). Compared to the Techtopian ideology, all social goals are absent in the Techspressive one. It’s a contrariety of individualism. Compared to the Work Machine ideology, the Techspressive sees technology as a highly pleasurable goal in its own right, while the former sees technology consumption from an unemotional, instrumental perspective. They therefore differ along a continuum of indulgence. Getting to know exactly what is in each of the four ideological points of the semiotic square can help profiling users in a more precise and optimized way, so that viral video campaigns can be targeted to specific behavioral fragments of each identity construct in order to maximize redemptions and participation rates. Knowing what brings users from one end to another in the ideological/identity square can help developing effective creative strategies for a video campaign, so that the number of responders is as high as possible. Roberto (1). Roberto defines himself as a heavy user, always connected and making frequent use of social technologies. While stating his overall opinions about what he called the “current digital social revolution” Roberto, 24, Italy, says: All this possibility to chat with people, keep in touch, even meet people, share our own personal stuff, see what’s up with buddies and so on is awesome, who would have ever thought this would have been made possible? However, sometimes, as a heavy-user of all these internet applications and hip websites, I do get to think it’s all just hyper-real, too cool to be true, in the end fake. So what I do when I think about that is to either use technology as a simple tool to get stuff done or I directly turn off the computer and go out and meet people. Once, some years ago, things were slightly different here. Making or keeping friends online was something one kept for himself, as a dirty little secret. Now it’s more and more common, it’s almost 50/50 with reality and I personally think that’s crazy. When it comes to the morale, Roberto tends to lock himself safe in observations and opinions on social technologies and their impact that are typical of contemporary Italian culture, which significantly leans towards Green Luddite attitudes. When, instead, it comes to technology itself and its power to connect and move people, Roberto becomes a stark Techtopian. Roberto (2). When talking about how much personal content he actually uploads to social tech websites and why he thinks he does that, Roberto starts from a Green Luddite, almost opportunistic position, and ends up contemplating a pleasure-oriented, playful and creative use of YouTube and Facebook. This is what he said: All in all I don’t put up that much stuff
  33. 33. 31 about what I am up to on the Facebook. And neither do I upload a lot of videos on YouTube. I am definitely not the protagonist of the daily news feed on Facebook’s homepage. But I created a “fake”, a character called Joe Triglia, and it’s all about the character. I think I do it most of all for the sake of playing, like a masquerade or something. But there sometimes I end up uploading some of the truest content I could produce, like personal diary entries, or some of my drawings. In this case, I guess it must be like those old blogs back in the late Nineties, where you would never get to know who the author was, and people were really talking about themselves behind a mask. Kelly and Brittany. Kelly and Brittany have never really been into the use of technology, and when they use it they said they tend to see it more as a tool for their real world than as a world for itself. YouTube has always been a place for laughs for them, or sometimes a huge reservoir to source from in order to broaden their knowledge of contemporary issues. Kelly had uploaded a video only once, and it was strictly functional to the aim of showing her parents how fun it was to be an exchange student overseas. Brittany had never uploaded a video , she even said she would not really know what to upload ever so she just watches. The two girls helped out Brett make and upload a video on YouTube. The video was about six guys from different nationalities singing parts of one of Brett’s songs, “When the Lights Burn Out”, in their own native language. This is what Kelly and Brittany had to say about the experience: You know, said Kelly, really I would never be doing what Brett does with YouTube (i.e. self-promoting his songs) but basically because I don’t have a talent of mine to promote on the internet. So then it’s obvious that Brett gets to know all the users on it and is very into it. I think it’s great that he can have such a tool, for free, to try pursuing his music career. As for me, like I said, I’m pretty much never on it except for when I have nothing to do with my time or some friend sends me a link so I go and watch it. But with Brett’s competition it was different. Brittany: Yes, it was different. Brett got his iPod stolen and he needed a new iPod, and this Chris Cendena competition came out on YouTube with an iPod as final prize so it was kind of automatic for us as soon as we knew about it to tell Brett he could rely on us if he wanted to do something unusual to try winning the competition. Kelly: We all got very involved in it, and wrote our own parts. Well, not all of us because I sung in American, so…but all the others did, we had Maori, Italian, Spanish, Dutch, it was awesome. That was really fun, each one of us singing a part of the song. We had a purpose I would say, and the purpose was helping Brett getting an iPod but we also became part of what he does so many times, taping himself when he’s singing a song and uploading it on YouTube. We didn’t win in the end, but it was very fun and definitely something far from the person I am that I would have probably never done in another situation. Kelly and Brittany have been taking a trip across the area in between Work Machine and Techspressive, which is where most of consumers might be, according to industry experts. What made them walk the line was certainly the whole situation, but perhaps the possibility of performing a new and fun task in a group and igniting future shared memories. Tommaso and Bianca: Tommaso makes a typical Work Machine use of Facebook and of YouTube. All the videos he had been uploading before our interview feature school buddies, jokes and funny moments he wants to share with his own friends using YouTube as a repository. Bianca uses YouTube only as a watcher, never checks users’ accounts and never uploads videos. She states she really appreciates the people who upload content, no matter what kind, since that makes YouTube extremely useful and/or entertaining to her, but she feels like she has never felt motivated enough to overcome her “Sicilian” laziness. This is,
  34. 34. 32 however, what she said about what we now can see as her own trip to the Techtopian end: Honestly, there was just about one single time in which I really was motivated into “giving” something, like contributing through uploading content. Crime Law Procedures is a seriously big exam at Law School here, so some guys decided to set up a wiki to share study materials, tricks, rumors about questions and so on. Well, I was surprised at myself for the frequency and the amount of stuff I was uploading. It was both because I felt that the more I was uploading the more useful the wiki would have turned out for me, and because the possibility of doing something like that felt revolutionary to me. Like you can really make a difference, an advantage, for a lot of people- since also other students in the next years are going to be using it- without having to give up anything of yours. I think that when I see a clearly defined group, a mission, an explicit role I can play- which is how I can make a difference- my contribution would really be valuable. So that’s when Bianca would upload stuff, doesn’t matter if video or text. Tommaso acknowledges that social technologies are culture bearers themselves, and is excited about the role they can play in breaking cultural barriers between people. However, his ordinary usage of websites like YouTube and Facebook is totally Work Machine. However, he has been adding some Techtopian routines lately: I think the best videos one could upload are collaborative viral videos. They are more (hesitates) meaningful, because then there is an end result of which you have been part of. Just like the Gmail video, or Terra Naomi’s “Say it’s possible”. Now, on the Facebook, I see its impact on cultures and habits could be gigantic, so I also join more “social” groups rather than just funny groups made up by friends of mine, and every now and then I make sure I leave some comments. I’m not a heavy commentator, but… Gaetano: I don’t have a Facebook account, sometimes I use MSN but basically I would rather talk on the phone or see people directly. You know, I’m from the South (of Italy), it’s always been very personal and face– to– face down there. I don’t look much into the things that I do when I’m online, like I have never thought a lot about why I do certain things or why I don’t do them, but I have to say that YouTube has always fascinated me. It has all that TV would never be able to give you: reality, entertainment, choice, interactivity, you and only you decide what should stay and what should go, plus YouTube is like a time capsule where you can find everything you feel like watching. I have used YouTube for some videos to show my friends down in Bari (Gaetano’s hometown in south-eastern Italy), one was a soccer lesson: how to place a good defense barrier on free kicks, the others were just to keep in touch with my buddies by showing them what I was up to and who I was hanging out with. You know, an image is worth one million words so… now I use YouTube mainly to share some sort of common feelings with my friends in a way more effective, however less “romantic”, than letters or chats. For Gaetano social technology is basically a waste of time: better to go out and meet people than checking up what they are doing through the Facebook. However, he experiences a shift towards the Work Machine corner when he exploits the great communicational potential of a YouTube video when he thinks about ways to more effectively share feelings and experiences with his far away friends. Fabio: When I use YouTube or any UGC social technology, I am really interested in reading or watching stuff that can give me some additional information about anything that’s going on that I probably wouldn’t get from TV. When it’s about uploading, however, it is a little different. Either it’s a simple waste of time, or I use YouTube as a repository and a “storage device” or I use it in a MySpace way, as a self-promotion to my songs (Fabio is an amateur hip-hop MC). But when I watched that Zeitgeist Illuminati documentary on YouTube I

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