Sport Science Review, vol.Sport
XXII,Science
no. 1-2,
2013,vol.
129XXII,
- 150 No. 1-2, April 2013
Review,
DOI: 10.2478/ssr-2013-0007
Success of Mixed Martial Arts
Video Topics on YouTube
Paweł ZEMBURA1
T
he purpose of this study was to identify if the YouTube viewership
is related to a subject of mixed martial arts (MMA) videos. To do so
passive and active viewership were featured, based on Checchinato, Disegna
& Gazolla (2009) work. Content analysis was used as the method and the
sample consisted of 200 most popular videos gathered from supreme canals
belonging to MMA organizations. Over half of the videos were classified
into previews and whole fights categories. The robust least square regression
explained 27% of passive viewership, and whole fights were the predictor of
highest passive attention. Just two categories were found significant as the
predictors of active viewership in the logit regression. Whole fights generated
more active response in contrary to previews. Pure sport-related videos were
generally found to generate higher interest among YouTube MMA spectators.
Keywords: martial arts, YouTube, viewership, logit regression
1 Jozef Pilsudski University of Physical Education, Warsaw, Poland.
ISSN: (print) 2066-8732/(online) 2069-7244
© 2013 • National Institute for Sport Research • Bucharest, Romania
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Mixed Martial Arts Video Topics on YouTube
“I think we’re gonna have another YouTube video coming soon!”
(Commentary on Yahir Reyes spectacular knockdown win at
Bellator mixed martial arts event on 8th of May 2009)
Introduction
Social media presence undoubtedly changed the area of mediated sports.
Among questions, related to these fresh technologies, the way how the social
media characteristic impacts features traditionally considered as appealing to
sport spectators is sought (Stauff, 2009). The most popular among video sharing
sites YouTube offers vast source of data for such studies, with over 4 billion
streaming per day (Oreskovic 2012), among which significant number is related
to sport. Using qualitative and quantitative content analysis we attempted to find
how content subject is impacting video success in nontraditional sport.
YouTube has been established in 2005, and ever since has grown and stayed
dominant among common video sharing sites, being third most visited website
after Google and Facebook (Fitzegard, 2012). Throughout that time the site
has been rejuvenated and social communication opportunities were added what
made it fit into Web 2.0 category as a content community (Kaplan & Haenlein,
2010). Nevertheless, the core of the idea holds its grounds and site is firstly the
area for watching and uploading video content as well as for commentating,
responding and assessing. From researcher perspective, it gives an access to vast
amount of primary data (Blythe & Cairns, 2009).
YouTube as an area of marketing draws challenging threads and represents
tremendous shift in sport media space (Mahan & McDaniel, 2006; Hutchins &
Rowe, 2012; Hutchins & Rowe, 2010). Differences like being a second source
of broadcast, constant role as a virtual community, decentralization of content
producer or selectiveness might be mentioned (Hutchins & Rowe 2009; Stauff,
2009). Despite, companies create and expose YouTube content to fulfill everpresent goals like building brand equity (Stauff, 2009; Waters & Jones, 2011).
On the other hand although the Internet is already widely recognized as
an important tool to keep company competitive on sport market (Filo & Funk
2005; Rein, Kotler & Shields, 2007; Coyle, 2010) some, even well-established
firms were utilizing it indolently (Ioakimidis 2010; Kriemadis, Terzoudis &
Kartakoullis, 2010). Unveiling YouTube content specific is especially important
for adolescent sports with social media oriented consumers, like mixed martial
arts (MMA). MMA experienced rapid growth mainly during the last decade
and has matured along with Internet and social media. Web-based canals of
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Sport Science Review, vol. XXII, No. 1-2, April 2013
promotion have been welcomed as a necessity, and frequently have been utilized
as a supreme tool in marketing (Santomier, 2008).
Findings about particular content attractiveness might be a step forward for
organizations to learn what draws YouTube viewers. Moreover, the study was
designed for better understanding of mediated experience among its consumers
(Rowe & Rowen, 2004). In our research we took advantage of video content
released by MMA event organizers, with an aim of giving an insight into its success.
Literature review
Literature concerning online video content was analyzed in order to make
research framework. Infancy of YouTube sport content as a research subject
forced to undertake the more general, sport-focused approach toward its
attractiveness for consumers. Based on this, the section about mixed martial arts
allure was extended.
Three main areas of research were taken into account in literature analysis.
First, reasons why viewers watch YouTube videos was unveiled. Then, why
that medium is crucial for marketing purposes. Finally, MMA attractiveness for
consumers was described.
Sport content on YouTube
Manual YouTube content analysis, which could give a detailed insight into
features dragging customers towards certain videos, was not frequently utilized
in a field of sport. Nevertheless, a basic concept of visiting a website as a selfselecting behavior, where only consumers who are attracted towards a particular
content will visit that Web site, gives a broad area for studies (McQuitty &
Peterson, 2000; Filo, Funk & Hornby, 2009). Consequently, some researches
were undertaken on recognizing new media attractiveness for sport consumers.
Those included problems why people seek sport content online (Carlson,
Rosenberger & Muthaly 2003; Hur, Ko & Valacich, 2007; Hong & Raney, 2007;
Seo & Green 2008; Clavio & Kian, 2010) or use specific forms of social media
(Clavio & Cooper 2010). Another intriguing subject was related to content itself,
detecting characteristic and aim of a message (Kassing & Sanderson, 2010;
Hambrick et al., 2010, Pegoraro, 2010). In most of these attempts uses and
gratification (McQuail 1984) and disposition theories (Bryant & Zillmann 2002)
were utilized as a research background. Despite differences related to media
characteristic and general research purposes some qualities of content were
distinguished, with entertainment and informativeness as magnetic values for
consumers (Earnheardt & Haridakis, 2008; Raney 2006; Ahn & Hong, 2007;
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Mixed Martial Arts Video Topics on YouTube
Hong & Raney, 2007). Entertainment is considered an especially complex
construct for a reason that various elements are gathered under its umbrella
(David, Horton, & German 2008; Raney 2006).
The YouTube lure pulling consumers into viewership might not be also
passed over. Alas, although the specificity of the communicational canal has
been recognized, content success-oriented researches haven not been frequently
conducted yet. In most cases content analysis on YouTube was utilized to unveil
the characteristic of message placed on it (Keelan, Pavri-Garcia, Tomlinson &
Wilson, 2007; Kim, Paek & Lynn, 2010; Waters & Jones 2011; Briones, Nan,
Madden & Waks, 2012).
In the field of sport Checchinato, Disegna and Gazzola (2009) made an
attempt to identify if a subject of a video impacts its success in terms of passive
and active enjoyment. YouTube content related to Italian football clubs playing
in first and second leagues during 2007/2008 season was brought as a sample.
Videos were manually divided into wide few categories based on the type of
content. Informative category occurred frequently among featured videos and
drew a lot of passive viewership. On the other hand, that category, quite similar
to television content, proved to be drawing relatively less active behavior among
consumers (Checchinato et al., 2009).
Regardless of identified main factors, complexion of sublime media
content along with particular sports characteristic demands developing suited
approach. The axiom stating that video success depends on content subject
dictated an analysis of what consumers are angling for in mixed martial arts.
The aim was to show YouTube as another way of viewing sports rather than just
locating it under unique media channel prevailing over its form. Such approach
was justified in up-to date researches about the sport, where consumers tended
to see other entertaining qualities of MMA than non-fans (Cheever, 2009). What
is more, it was recognized that entertainment, as a crucial ingredient attracting
consumers to various sports needs fitting avenue (Beck & Bosshart, 2003, Brock
& Livingston, 2004).
Mix martial arts and social media consumers
Although mix martial arts (MMA) in its present, commercial form have
origins in United States, tremendous pace of growth has established it as a
popular mediated sport across the globe, including Canada, Brazil, Poland and
Malaysia (Thomson & Baker, 2010). The introduction of MMA is usually linked
with establishing the UFC, present hegemon in that field and for many synonym
to the sport, in 1993. Starting with a no-hold-barred fights image it developed
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Sport Science Review, vol. XXII, No. 1-2, April 2013
into mainstream sport and entertainment by decreasing brutality, developing
the set of strict rules, and being sanctioned by athletic commissions (Thomson
& Baker, 2010). Its achievements since 2005 have encouraged many smaller
organizations all over the world to participate in the sport development and to
seek their own path of growth.
With such a minute history mixed martial arts might be classified as a new
sport. It refers also to its consumers, mainly males between 18-35, who are
frequently considered the most attractive segment in terms of sport revenues
(Cheever, 2009; Kim, Greenwell, Andrew, Lee & Mahony, 2008; MacIntosh
& Crow, 2011). MMA fans grew up and entered new technologies along with
the sport, benefiting from various media outlets (Thomson & Baker, 2010).
Many organizations took advantage of it putting a lot of attention into social
media: exposing free parts of their live broadcast along with advertisements on
Facebook, throwing full fight replays, highlights, extended previews and shows
on YouTube and encouraging athletes in Twitter use.
Sources confirmed accuracy of interest given to social media in this sport
(Santomier, 2008). MMA consumers are among most intensively exploiting social
media. As found in Catalyst Public Relations study 40% of avid MMA fans used
YouTube to follow and discuss the sport, what made them the most YouTubeoriented rooters (Broughton, 2012). MMA fans and basketball supporters are
also most likely to follow simultaneously the game or event on social media
while watching it (Broughton, 2012). It makes YouTube potentially the valuable
social media in terms of bringing consumers in front of TV sets.
MMA spectatorship
Some researches concerning what do consumers seek in MMA were
undertaken. First, attendees on the events were taken as a sample. Motivational
approach, being one of the most accurate ways of exploiting spectators behavior
(James & Ross, 2004), was used in Kims et al., (2008; Kim, Andrew & Greenwell,
2009) and Andrew, Kim, S., O’Neal, Greenwell & James (2009) researches. Sport
interest, drama and socializing were found the most important among US local
event spectators by Kim el al. (2008). In his following study, he found different
motives leading into predicted MMA media consumption between Korean and
American spectators. Although similarities appeared, with sport interest as the
leading motive regardless of the country (Kim et al., 2009), fighter interest and
drama followed it as significant predictors of consumption in US while drama
and adoration were distinguished in Korea. Andrew et al. (2009) conducted
his research on a professional event in US, identifying aesthetics, drama,
escape, vicarious achievement as the highest ranked motives among spectators.
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Aesthetic and knowledge were described as the best predictors of MMA media
consumption. MacIntosh and Crow (2011) found entertainment, drama and
skill as the most perceived spectators motives on an amateur event. In stepwise regression, only social interaction was recognized as a significant predictor
of intentions to return to a similar show. Uses and gratification theory was
utilized to study emotions and risk taking impact on MMA television viewers
attitudes and consumption. Both arousal and pleasure significantly impacted
spectators attitudes towards event, and positive attitude influenced directly
media consumption (Lim, Martin & Kwak, 2010).
Online survey was used by Cheever (2009) to seek attitudes, behaviors
and opinions in a big sample of regular mixed martial arts viewers. The main
reasons which made avid MMA viewers watch the sport were “compilation of
martial styles” and “competition of the sport”. Most entertaining aspects of
the spectacle were “skills of the fighters” (90%), their “technique” (82%) and
“fighting styles” (82%). Vastly smaller percentage was entertained to the sport by
violence (19%), “watching the men beat each other up”, “seeing someone hurt”
or by “blood” (13%).
Regardless of the way of consuming MMA and tool used in research,
drama, entertainment and sport interest were usually what encouraged viewers
to the sport. What is also eye-opening, MMA fans decidedly varied from nonfans in describing violence in the sport, viewing it rather as a technical sporting
battle (MacIntosh & O’Reilly, 2012). Based on this some implications towards
YouTube content attractiveness could be made. Strong relation with overall sport
essence alike competition-related attributes were drawn in up-to-date MMA
spectatorship analyses (Kim et al., 2008; Andrew et al., 2009; Cheever 2009;
MacIntosh & Crow 2011). That scheme transferred into YouTube surface could
result in success of videos being replays or highlights of the games. Nevertheless,
video content analysis in MMA has not been utilized yet, and it might give a new
outlook on this subject.
Methods
Research questions
Transferring consumers interest into indicators related to viewership
the content analysis was utilized, to seek the most attractive video themes of
particular sport on YouTube. To do so in the research focused on content,
attractiveness had to be operationalized as a result of actions undertaken by the
consumers. Both passive and active content success was taken into account to
exceed the analysis and understanding for uniqueness of the medium.
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Sport Science Review, vol. XXII, No. 1-2, April 2013
RQ1. Does the content of videos have influence in their success in terms
of passive viewership?
RQ2. Does the content of videos have influence on active viewership?
Sampling technique
In the study YouTube official channels owned by mixed martial arts
organizations were used as a sample. The collection of videos was purposive
what was driven by searching the most popular videos from channels receiving
the most views. The sample consisted of videos put into channels with an
aggregated number of over 200000 views. Although few organizations owned
or co-owned few channels, related to fighters, broadcasters or reserved for indepth previews, exclusively the main one was analyzed. Only channels belonging
to up-to-date existing organizations were taken under consideration through
content generally lost its attractiveness with time. Links towards YouTube
channels were found on official sites and if not, names of organizations were
put into the website searching engine. That engine allows distinguishing most
viewed videos related with tags, words in the title and categories. The number
of views for each video is also accessible. Search was made on 29th August,
2012 when also general analysis of relevant video channels was conducted.
Twenty videos which received the most views from every canal were analyzed.
A quantitative description of the data was based on statistics available for every
video on YouTube. Following data was collected: number of views, day of
upload, number of comments, total amount of ratings and number of being
tagged as a favorite.
Qualitative content analysis: content themes Aforementioned lack of literature regarding YouTube sport videos forced
to build new categories fitting goals in the research. Content analysis was used
to manually classify videos into fitting categories based on semantic themes
and structural features (Bauer, 2000). It is a well-known method for examining
qualitative data, frequently used in studies of mass media (Blythe & Cairns 2009;
Jarett 2010). In an online context it might lead to identification or discussion
about categories of examined content (Parker, Saundage & Lee, 2011). In the
given sample similarities among video could be observed regardless of the
company. During analysis particular types of content were identified. Categories
of content used in mediated sport arguably did not fit into research, due to
their generality and consumer-based approach. From content-related point of
view contrary categories like emotional/rational might be considered subjective
(Checchinato et al. 2009). That is why a low level of abstraction in defining
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Mixed Martial Arts Video Topics on YouTube
coding categories was used (Parker et al. 2011). The team of three doctoral
students with education related to sport and acknowledged with MMA worked
on categories constructs.
Table 1
Content categories of MMA video placed on YouTube
Category of content
Description
whole fights (WF)
whole fight replay
highlight related to one fight (FO)
selected, incomplete content from just one fight
highlights related to an event or a selected content from more than one fight, concentrated on pure
fighter (FA)
entertainment (excluding interviews etc.)
celebration related content (CE)
opening ceremonies, win celebration, fighter entrances, ring girls
appearances
fighters introductions (FI)
videos related to a fighter as a star, related to his activities,
lifestyle, hobby etc.
interviews (IN)
interview with a fighter or someone else from MMA community
(like promoter or ring girl)
conferences (CO)
pre- and post-fight conferences and accidents during them
behind the scenes materials (BS)
in-depth look into events, around event materials like ring girls
selection and event preparations
previews/trailers/primetime (PT)
content shown before an event: fighters preparations towards
upcoming fight, hype videos, films about organization, directed
films about an upcoming event
Categories of sport content themes were transferred in the process of
creating dichotomous variables from categorical variables, called dummy coding.
Every video was classified into one category. Then, since every video was put
into just one category, it was coded as 1 in this category and 0 in others.
Measurement
Passive enjoyment. Indicators for measuring passive and active enjoyment
were partially adapted from previous research. Since website success depends on
company aims (Cothrel, 2000), for YouTube content it is crucial primary to gain
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Sport Science Review, vol. XXII, No. 1-2, April 2013
exposure. Passive content success was described with video number of views, a
statistic which is accessible for every YouTube video website (Checchinato et
al., 2009). Video success was considered to be a result of consumer demand.
Amount of video views was consequently the effect of consumer consciously
and actively seeking content (Stafford, Stafford & Schkade 2004; Scott 2007;
Chiu, Cheung, & Lee, 2008).
Views are associated to the general concept of site exposure, that refers
to the total number of visits at a Web site in a time period, without regard to
visitor duplication and that can be used as a metrics of site’s success (Novak &
Hoffman, 1996). Traffic is a popular factor of website success, and views on
YouTube represent it well (Alpar, Porembski & Pickerodt, 2001).
In passive enjoyment measurement, views were taken as a dependent variable.
Precisely, it was the total number of views that video has received per day since
it has been launched. As independent variable favorite (F) was utilized, which
means the number of times a single video has been recommended. Checchinato
and team (2009) brought this factor justifying that the video marked as a favorite
resource by a user is likely to increase its overall awareness (Cheng, Dale & Liu
2008a). Other independent variables were made of video content categories
transformed into dummy variables.
Active enjoyment. Number of ratings (R), comments (C) and favorites (F)
marks better manifest actual user behavior. Such activities require additional
effort from consumers, so their numbers are considerably lower than amount
of views, still represent well more committed approach. These three indicators
have a similar distribution in time with tails dropping sluggishly comparing to
the simple number of views (Cheng, Dale & Liu 2008b). Active video enjoyment
was described in past by Index of Activity (IA), created to understand how many
views are necessary to receive an active feedback from the users (Checchinato et
al., 2009). Nonetheless, it was decided to invert it and instead of V being a divisor
it was made a dividend. That way, a higher Activity Index (AI) result represented
higher activity of the users what made it easier to interpret. AI=(C+F+R)/V, where
day;
i = single video;
V - views- average number of Views per day since being launched;
C - comments — the total number of comments received by the video, per
F - favorite — the number of people who indicate that video i is their
Favorite, per day;
R - number of ratings — the total number of ratings that i has received,
per day.
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The logit regression model was applied to answer RQ2. Activity Index was
used as an dependent variable. It was transferred into dummy variable, where
“1” was given if the single video AI was over median for the sample, and “0” if
the video AI was equal or lower from median in the sample. As independent
variables dummy variables representing each content category were used.
Sample description
The sample consisted of 200 videos placed on 20 channels. These twenty
biggest channels in terms of overall viewership were owned by currently working
MMA event organizers. Professionalization among those organizations varied
from global companies with international reach and presence in mainstream
television broadcast to regional organizations using YouTube as a tool to
document their events. It was echoed by discrepancies between videos. Although
the first notion was that the sample would consist of videos from professional
organizers, the overall market was found minute, and few local initiatives were
placed in the sample as well. Same dissimilarity was found in place of origin
even though most enterprises had roots in US, other were from Europe, Asia
and Africa. The featured videos were present on YouTube from 10 to 2200 days.
Table 2
Variables description
Arithmetical
mean
St. deviation
Median
Min.
Max.
Views per day
614,04
1176,37
99,69
1,97
6991,75
Ratings per day
1,11
2,69
0,15
0
24,91
Comments per day
0,84
1,76
0,09
0
14,78
Favourites per day
0,42
2,09
0,04
0
27,89
Index of Activity
0,0036
0,0027
0,0029
0,0003
0,0138
In the sample previews and whole fights were represented by far most
frequent. Those two categories were subject to over half of videos in the sample.
Less present were highlights from one fight, materials about fighters and behind
the scenes materials. Conferences, interviews and celebrative content were not
found popular.
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Table 3
Content categories load
Content
WF
HO
HE
CE
FI
IN
CE
BE
PT
Factor load
24%
11%
8%
2%
10%
4%
7%
9%
27%
Previews and highlight related to one fight themes were receiving highest
passive interest. While videos in the first category were averagely most viewed,
those related to the second received on average most active interest. Celebration
and fighters introductions were the least popular in terms of passive viewership,
but received relatively high AI.
Table 4
Average values of descriptive variables according to the various video categories
Content category
V
R
C
F
AI
Whole fights
418,01
1,29
0,87
0,40
0,0053
Highlight related to one fight
1117,76
2,23
1,39
2,10
0,0032
Highlights related to an event or fighter
322,58
0,51
0,40
0,13
0,0031
Celebration
29,92
0,09
0,06
0,06
0,0038
Fighters introductions
97,72
0,18
0,12
0,05
0,0037
Interviews
240,32
0,57
0,62
0,03
0,0020
Conferences
759,31
0,75
1,18
0,08
0,0033
Behind the scenes
154,69
0,11
0,09
0,10
0,0033
Previews
1289,15
1,56
1,23
0,24
0,0027
AVR
677,95
1,11
0,84
0,42
0,0036
The correlations between variables excluding AF were positive, but the
strength of relationships differed. It ranged from 0,44 to 0,91, the strongest
between ratings and comments and weakest between views and favorites. AF
was negatively correlated with all other variables, and the relation was strongest
with views, what suggested that less frequently viewed videos were relatively
more popular in terms of active enjoyment.
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Table 5
Correlation matrix of variables describing the videos
V
1,0000
F
0,4430
1,0000
R
0,7623
0,7701
1,0000
C
0,8143
0,7022
0,9191
1,0000
AI
-0,2132
-0,0540
-0,0916
-0,1145
1,0000
V
F
R
C
AI
Results
To answer whether content success is related to its theme robust least
square regression was conducted in Gretl. Before that, one of the videos was
excluded from the sample for being an outlier, since it had twice that many
views as secondly ranked video. After manual backward regression to remove
noncontributing variables the model explained 27% of the variances. Highlights
related to one fight, previews, interviews were excluded from the model. Except
Const only F was impacting positively V. Significant independent variables could
be categorized from least to most negatively impacting predicted number of
views. In this case whole fights, highlights related to more than one fight and
interviews were less negatively impacting the independent variable. On the
other hand, videos belonging to celebration, fighters introduction and behind
the scenes material categories were decreasing the number of views most
importantly.
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Table 6
Passive content viewership regression model
Coefficient
St. error
t-test
p value
Const
875,062
153,357
5,7061
<0,00001
Favourites
231,106
43,2608
5,3422
<0,00001
whole_fights
-549,971
175,284
-3,1376
0,00197
highlights_rela
-583,422
228,414
-2,5542
0,01142
celebration_eve
-858,961
153,095
-5,6106
<0,00001
fighters_introd
-788,399
154,023
-5,1187
<0,00001
Interviews
-642,709
203,912
-3,1519
0,00188
behind_the_scen
-743,98
177,132
-4,2002
0,00004
Note. r²= 0,2736, number of observations=199, p value<0,05
Than the Gretl logit regression model was calculated to search if content
theme impacted active feedback from the users. The r² value after backward
elimination was estimated on about 0,05, which is very low.
Whole fights category was positively impacting active viewership while
previews negatively influenced its number. Amount of good prediction using
that model was estimated on 60,3%. Chi² test also provided differences between
Activity Index regarding these two variables at p<0,05 level. Whole fights were
significantly more actively viewed while previews were relatively less enjoyed.
Table 7
Active viewership robust logistic regression model
whole_fights
previews_traile
Coefficient
St. error
Z
p value
0,887303
-0,581921
0,317554
0,286432
2,7942
-2,0316
0,0052
0,0422
Note. r²=0,0467; number of observations=199; p<0,05
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Discussion
Considering still-growing size of social media and their already recognized
importance in marketing and social contexts YouTube content appears to be
meaningful research subject. The reason for this is that content is universally
recognized as a factor influencing media consumption (Urban 1981). This study
aimed at identifying if content subject impacts a passive and active video success.
Although recognized models were not strong predictors, results related to MMA
were definitely interesting and elucidated approach into a specific content analysis.
First of all, since the sample consisted of most watched videos on ascendant channels, what was perceived synonymously with most successful, some
findings might be made. Two
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kinds of categories were most popular in the sample: previews - 27% and whole fights - 24%. Previews and highlights related to
one fight were on average most viewed videos. On the other hand, mean of
views is not a good way to identify most popular categories because organization
size factor seems to be most important in this instance and was not exploited in
the research. Whole fights and highlights related to one fight are both pure-competition related contents, which shows importance of such from the marketing
perspective. The crucial implication is that the spectators are attracted to the
essence of sport event, which is probably produced by-the-way, so additional
exertion must be made to make sure that high-quality documentary content is
placed on channel.
The relative Activity Index showed whole fight as a category which brought
the most active response among categories. Executed logit regression proved also
that the category impacted positively attention towards videos while previews
impacted it negatively. This result was not similar to previous findings where
content almost the same as television-based was proven to be drawing less active
attention (Checchinato et al., 2009). The reason might be that many of the video
content related to the MMA organizations in opposition to football content
were impossible to reach otherwise than by YouTube. Similar examples of that
situation were observed by Stauff (2009) where sport competition content
placed exclusively on YouTube received a lot of attention.
Low amount of exactly explained independent variables by the logit
regression model in the research might be interpreted in comparison to previous
attempt on the subject. First, other approach was undertaken by Checchinato et
al. (2009) who included all channels related to the research subject in the sample.
In our research sample consisted just on 199 videos on 20 channels, while in the
first study, 374 videos from 125 channels were taken into account.
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Another reason of such minute r² in our research could be related to higher
number and more rigorous approach towards content categories. In this case,
problem with informative and entertainment division between content might
be well observed since categories in the research could be probably classified
into both of them (Ahn & Hong, 2007). The same problem appears with
another general classification of online content, informational and emotional
(Devasagayam & Buff, 2008). The categories used in the study were focused on
video content and plot building that way the separable assemblages. Previously
applied, but not-fitting categories like “fans starring in the videos” were
abandoned, although they could probably better describe content differences.
Approach exclusively focused on video themes was undertaken to identify the
categories. Also, only 5 categories of content were used in Checchinato et al.
(2009) study comparing to 9 in this one. In the result only two of them were
found significant in the model of active enjoyment. What is important, these
two predictors were highest loaded factors as well. The reason of bad fit of the
model might be somewhat related to video success factors not included in the
study. Checchinato et al. (2009) employed three areas of content success, namely
its subject, source and recommendation. Video producer was found to be an
important independent variable in the Italian research. If video was generated
by user, it was reported to be less actively enjoyed by viewers. Also, both official
and not official channels were used as additional variable. Factors which possibly
might influence both dependent variables used in paper could be related to the
organization. That includes its size, overall attitudes and importance of YouTube
in their strategy, video production features, video quality, content distribution
restrictions. Excluding this factor might help in researches aiming recognition
of content attractiveness.
To sum up, content subject on YouTube does not tend to be the main
factor of sport video success. Nevertheless, factors previously associated with
mediated sport content attractiveness like entertainment, suspense, drama must
be rethought because of YouTube specific (Peterson & Raney 2008; Raney
2006). On the one hand, YouTube might very well fulfill previous sport theories,
like fight previews being an example of sport enhancing experience found in
entertainment theory. In the study pure-competition related videos were found
most successful. On the other, the new communicational platform might
undoubtedly prevail on to date mediated sport theories (Stauff, 2009).
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Paweł ZEMBURA is a PhD student at Jozef Pilsudski University of Physical Education
in Warsaw, specializing in sport management. He received a MA in economic geography
from University of Warsaw as well as MA in tourism and leisure studies from Jozef
Pilsudski University of Physical Education. Area of his current research interest is
related to sport consumer behaviors. Before enrolling in PhD programme he worked in
sport industry owning a fitness company. He can be contacted at:
Corresponding address:
Paweł Zembura
ul. Czorsztynska 8/16
01-410 Warsaw
Poland
Phone: +48 698168242
E-mail: [email protected]
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