visualizing sports rivalry with social network analysis
DESCRIPTION
Tyler, B.D. & Cobbs, J. 2014. "Visualizing rivalry intensity: A social network analysis of fan perceptions," North American Society for Sport Management (NASSM) Annual Conference, Pittsburgh, PA. Central to the conceptualization of rivalry is the process of social categorization and seeing the self and others as members of ingroups and outgroups. For some sport fans—especially those deemed highly identified—a favorite team becomes an extension of one’s self, and opposing teams and their fans are seen as dissimilar outgroups. Akin to other definitions, we view a rival as being a highly salient outgroup that poses an acute threat to the identity of the ingroup. To bring further clarity and consistency to the rivalry discussion, we quantify the perceived rivalries within a closed network of organizations by surveying college football fans (n=5,317) from 122 Football Bowl Subdivision (FBS, or Division I-A) teams using on an online questionnaire posted on 194 fan message boards. Through employing social network analysis (SNA), we graphically map rivalry scores in Netdraw and conduct further statistical analysis via UCINET SNA software. The network analysis results are most interesting when viewed graphically as nodes (universities) with bi-directional ties among them of various magnitude. In the study, we employ SNA measures of ego networks, centrality and power to reveal insights about the nature of rivalry.TRANSCRIPT
North American Society for Sport Management. Pittsburgh, PA. Friday, May 30, 2014
Visualizing rivalry intensity:
A social network analysis of fan perceptions
Joe B. CobbsNorthern Kentucky
University
B. David TylerWestern Carolina
University
Tyler & Cobbs 2NASSM 2014, Pittsburgh, PA
What is rivalry? What’s a rival?
…an actor which increases the focal actor’s
psychological involvement…
Kilduff et al., 2010
outgroup
Luellen & Wann, 2010
disliked competitor
Dalakas & Melancon, 2012
adversarial relationship… gaining significance through competition, incidences, proximity,
demographic makeup, or historical occurrences
Havard et al., 2013
I know it when I see it
Forrest et al., 2005
A highly salient outgroup that poses an
acute threat to the identity of the ingroup
or to ingroup members’ ability to
make positive comparisons between their group and the
outgroup
Tyler & Cobbs, under review
Divisional opponent
McDonald & Rascher,
2000
Shared border
Morley & Thomas, 2007
Teams under 20 mi. apart
Baimbridge et al.,
1995
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Why do we care? – Demand estimation
𝐴=𝛽0+𝐵𝑋+𝑒
Tyler & Cobbs 4NASSM 2014, Pittsburgh, PA
Why do we care? – Behavior toward rivals
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Why do we care? – Driving consumption
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Why do we care? – Limit fan aggression
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Why do we care? – Sponsor activation
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Why do we care? – Contract incentives
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How can we know a rivalry’s intensity? Binary approaches• Shared border• Divisional opponent• Naming rivalries
Variable approaches• Distance• MRI (hasn’t been done)
• Collecting data on specific dyads (current study)
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METHOD
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Method - Population Surveyed college football fans (n=5,317) 122 FBS (DI-A) teams 194 fan message boards
Identified with favorite team (µ=5.2/7.0)
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Method – Rivalry points allocation
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RESULTS
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Dyadic relationships
44.2
2.959.3
32.5
25.4
0.7
Sees other as a rival
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Dyadic relationships
16.8
4.066.8
68.8
90.7
0.3
Sees other as a rival
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National Rivalry Network
Line width: average point allocation (> 5; 100 max)Node size: in-degree centralityNode color: conference
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Most focused rivalriesBased on aggregate score
159.6
171.8
182.6
#3
#2
#1
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Biggest rivals
Line width: average point allocation (>50 in either direction; 100 max)
Node size: in-degree centralityNode color: conference
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Ego networksWisconsin – most ‘cohesive’ ego network
(density=81.9)Rivals connected to other rivalsTie strength > 5
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Ego networksWisconsin – most ‘cohesive’ ego network
(density=81.9)Rivals connected to other rivalsTie strength > 3
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Social capital
Notre Dame – 2nd most powerful network
Bonacich power: est. social capital by centrality of alters
Alabama most powerfulTie strength > 5
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SEC Network (tie >5)
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DISCUSSION
Map from http://plvcolin.blogspot.com
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Implications Nature of “rivalry” Start of a parsimonious measure of rivalry Marketing & sponsorship Event management League structure• Conference realignment, promotion & relegation
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Next steps Refine survey based on findings Extend to other sport leagues Increase knowledge of rivalries themselves
(e.g., antecedents)
North American Society for Sport Management. Pittsburgh, PA. Friday, May 30, 2014
Visualizing rivalry intensity:
A social network analysis of fan perceptions
Joe B. CobbsNorthern Kentucky
University
B. David TylerWestern Carolina
University